General Keywords

[ Algorithms ] [ Algorithms; Optimization ] [ Applications ] [ Data, Challenges, Implementations, and Software ] [ Deep Learning ] [ Deep Learning; Deep Learning ] [ Neuroscience and Cognitive Science ] [ Optimization ] [ Optimization; Optimization ] [ Probabilistic Methods ] [ Probabilistic Methods; Probabilistic Methods ] [ Reinforcement Learning and Planning ] [ Social Aspects of Machine Learning ] [ Theory ] [ Theory; Theory ]

Topic Keywords

[ Active Learning ] [ Active Learning; Algorithms ] [ Activity and Event Recognition ] [ Adaptive Data Analysis; Optimization ] [ Adversarial Examples ] [ Adversarial Learning ] [ Adversarial Learning; Algorithms ] [ Adversarial Networks ] [ Adversarial Networks ] [ Adversarial Networks; Deep Learning ] [ Adversarial Networks; Deep Learning ] [ AI Safety ] [ Algorithms Evaluation ] [ Approximate Inference ] [ Architectures ] [ Attention Models ] [ Audio and Speech Processing ] [ AutoML ] [ Bandit Algorithms ] [ Bandit Algorithms; Algorithms ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandits ] [ Bayesian Deep Learning ] [ Bayesian Methods ] [ Bayesian Nonparametrics ] [ Bayesian Theory ] [ Bayesian Theory ] [ Benchmarks ] [ Biologically Plausible Deep Networks ] [ Biologically Plausible Deep Networks; Deep Learning ] [ Biologically Plausible Deep Networks; Neuroscience and Cognitive Science ] [ Body Pose, Face, and Gesture Analysis ] [ Body Pose, Face, and Gesture Analysis; Applications ] [ Boosting and Ensemble Methods ] [ Boosting and Ensemble Methods; Algorithms ] [ Boosting and Ensemble Methods; Probabilistic Methods; Probabilistic Methods ] [ Causal Inference ] [ Classification ] [ Classification; Algorithms ] [ Classification; Algorithms ] [ Classification; Applications ] [ Classification; Deep Learning; Deep Learning ] [ Classification; Deep Learning; Deep Learning ] [ Clustering ] [ Clustering; Applications ] [ Clustering; Theory ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Theory ] [ Cognitive Science; Neuroscience and Cognitive Science ] [ Collaborative Filtering ] [ Collaborative Filtering; Algorithms ] [ Collaborative Filtering; Applications ] [ Combinatorial Optimization ] [ Components Analysis (e.g., CCA, ICA, LDA, PCA) ] [ Computational Biology and Bioinformatics ] [ Computational Biology and Bioinformatics; Applications ] [ Computational Complexity ] [ Computational Learning Theory ] [ Computational Photography ] [ Computational Social Science ] [ Computer Vision ] [ Computer Vision; Applications ] [ Computer Vision; Applications ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Continual Learning ] [ Convex Optimization ] [ Convex Optimization; Optimization ] [ Convex Optimization; Probabilistic Methods; Theory; Theory ] [ Convex Optimization; Theory ] [ Crowdsourcing ] [ Decision and Control ] [ Deep Autoencoders; Deep Learning ] [ Deep learning Theory ] [ Deep RL ] [ Density Estimation ] [ Density Estimation; Deep Learning ] [ Derivative Free Optimization ] [ Dialog- or Communication-Based Learning ] [ Dimensionality Reduction ] [ Distributed and Parallel Optimization ] [ Distributed Inference ] [ Efficient Inference Methods ] [ Efficient Training Methods; Deep Learning ] [ Embedding and Representation learning ] [ Embedding Approaches ] [ Exploration ] [ Fairness, Accountability, and Transparency ] [ Fairness, Accountability, and Transparency ] [ Few-Shot Learning ] [ Few-Shot Learning; Algorithms ] [ Frequentist Statistics ] [ Game Theory and Computational Economics ] [ Gaussian Processes ] [ Gaussian Processes and Bayesian non-parametrics ] [ Generative Models ] [ Generative Models ] [ Graphical Models ] [ Graphical Models ] [ Hardware and Systems ] [ Healthcare ] [ Human or Animal Learning ] [ Human or Animal Learning; Probabilistic Methods ] [ Image Segmentation ] [ Image Segmentation; Algorithms ] [ Image Segmentation; Applications ] [ Information Theory ] [ Kernel Methods ] [ Kernel Methods; Optimization ] [ Large Deviations and Asymptotic Analysis ] [ Large Scale Learning ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Applications ] [ Large Scale Learning; Deep Learning ] [ Large Scale Learning; Probabilistic Methods ] [ Latent Variable Models ] [ Learning Theory ] [ Markov Decision Processes ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Matrix and Tensor Factorization ] [ MCMC ] [ Memory ] [ Memory; Optimization ] [ Meta-Learning ] [ Meta-Learning; Applications ] [ Metric Learning ] [ Missing Data; Algorithms ] [ Missing Data; Algorithms ] [ Missing Data; Theory ] [ Model Selection and Structure Learning ] [ Models of Learning and Generalization ] [ Monte Carlo Methods ] [ Multi-Agent RL ] [ Multimodal Learning ] [ Multitask and Transfer Learning ] [ Multitask and Transfer Learning; Algorithms ] [ Multitask and Transfer Learning; Probabilistic Methods ] [ Multitask, Transfer, and Meta Learning ] [ Natural Language Processing ] [ Network Analysis ] [ Networks and Relational Learning ] [ Neural Coding; Neuroscience and Cognitive Science ] [ Neuroscience ] [ Neuroscience and Cognitive Science ] [ Non-Convex Optimization ] [ Non-Convex Optimization ] [ Non-Convex Optimization; Theory ] [ Non-parametric models ] [ Object Detection; Deep Learning ] [ Object Detection; Neuroscience and Cognitive Science ] [ Online Learning ] [ Online Learning Algorithms ] [ Online Learning Theory ] [ Online Learning; Theory ] [ Optimal Transport ] [ Optimization for Deep Networks ] [ Others ] [ Others ] [ Others ] [ Others ] [ Others ] [ Planning and Control ] [ Plasticity and Adaptation ] [ Predictive Models ] [ Predictive Models; Deep Learning ] [ Predictive Models; Deep Learning ] [ Privacy, Anonymity, and Security ] [ Privacy, Anonymity, and Security ] [ Probabilistic Methods ] [ Probabilistic Programming ] [ Program Understanding and Generation ] [ Quantitative Finance and Econometrics ] [ Ranking and Preference Learning ] [ Ranking and Preference Learning; Theory ] [ Reasoning; Optimization ] [ Recommender Systems ] [ Recurrent Networks ] [ Recurrent Networks; Theory ] [ Regression ] [ Regression; Algorithms ] [ Regression; Applications ] [ Regression; Optimization ] [ Regression; Probabilistic Methods; Probabilistic Methods ] [ Regularization ] [ Regularization ] [ Reinforcement Learning ] [ Reinforcement Learning and Planning ] [ Relational Learning ] [ Representation Learning ] [ Representation Learning; Algorithms ] [ Representation Learning; Algorithms ] [ Representation Learning; Neuroscience and Cognitive Science ] [ Representation Learning; Neuroscience and Cognitive Science; Neuroscience and Cognitive Science ] [ Representation Learning; Optimization ] [ RL, Decisions and Control Theory ] [ Robotics ] [ Robust statistics ] [ Semi-Supervised Learning ] [ Social Aspects of Machine Learning ] [ Software Toolkits ] [ Spaces of Functions and Kernels ] [ Sparse Coding and Dimensionality Expansion; Applications ] [ Sparsity and Compressed Sensing ] [ Sparsity and Compressed Sensing; Applications ] [ Sparsity and Compressed Sensing; Optimization; Theory ] [ Speech Recognition ] [ Statistical Learning Theory ] [ Statistical Physics of Learning ] [ Stochastic Optimization ] [ Structured Prediction ] [ Submodular Optimization ] [ Supervised Learning ] [ Sustainability and Environment ] [ Theory ] [ Time Series Analysis ] [ Time Series Analysis; Deep Learning ] [ Time Series Analysis; Probabilistic Methods; Probabilistic Methods ] [ Time Series and Sequences ] [ Topic Models ] [ Uncertainty Estimation ] [ Uncertainty Estimation; Applications; Probabilistic Methods ] [ Unsupervised Learning ] [ Unsupervised Learning; Applications ] [ Unsupervised Learning; Deep Learning ] [ Variational Inference ] [ Visualization or Exposition Techniques for Deep Networks ] [ Visual Question Answering ] [ Visual Scene Analysis and Interpretation ]

1393 Results

Expo Workshop
Sun 5:00 High-Quality Data Labeling at Scale with Toloka
Olga Megorskaya, Saiph Savage, Omar Alonso, Daria Baidakova, Dmitry Ustalov, Vladimir Losev, Oleg Pavlov, Kate Saenko
Expo Talk Panel
Sun 5:00 Machine Learning for Addressing Power Grid Congestion
Chris Davis
Expo Workshop
Sun 5:00 Real World RL: Azure Personalizer & Vowpal Wabbit
Sheetal Lahabar, Etienne Kintzler, Mark Rucker, Bogdan Mazoure, Qingyun Wu, Pavithra Srinath, Jack Gerrits, Olga Vrousgou, John Langford, Eduardo Salinas
Expo Talk Panel
Sun 7:00 Unique Research Opportunities in AI Algorithms, Health, Traffic, and Weather
Johannes Brandstetter, Sepp Hochreiter, Michael Kopp, David P Kreil, Alina Mihai
Expo Talk Panel
Sun 10:00 IBM Analog Hardware Acceleration Kit
Kaoutar El Maghraoui, Malte J Rasch
Expo Talk Panel
Sun 17:00 Enterprise-Strength Federated Learning: New Algorithms, New Paradigms, and a Participant-Interactive Demonstration Session
L W, Nathalie Baracaldo, Chaitanya Kumar, Parijat Dube, Mikhail Yurochkin, Theodoros Salonidis, Shiqiang Wang
Expo Workshop
Sun 17:00 PaddlePaddle-based Deep Learning at Baidu
Dejing Dou, Chenxia Li, Teng Xi, Dingfu Zhou, Tianyi Wu, Xuhong Li, Zhengjie Huang, Guocheng Niu, Ji Liu, Yaqing Wang, Xin Wang, Qianwei Cai
Expo Workshop
Sun 17:10 PaddleCV: Rich and Practical CV Models from Industrial Practice
Chenxia Li
Expo Talk Panel
Sun 17:43 Live-action Demo with Audience Participation: Jointly train an FL model using algorithms presented in the lightning talks
Expo Workshop
Sun 18:30 Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond
Xuhong Li
Expo Workshop
Sun 20:20 Paddle Quantum: Towards Quantum Artificial Intelligence
Xin Wang
Tutorial
Mon 8:00 Continual Learning with Deep Architectures
Vincenzo Lomonaco, Irina Rish
Tutorial
Mon 8:00 Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
Ahmed M. Alaa, Mihaela van der Schaar
Tutorial
Mon 8:00 Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning
Ahmed M. Alaa, Mihaela van der Schaar
Affinity Workshop
Mon 10:30 Ceramic Cracks Segmentation with Deep Learning
Gerivan Junior, Janderson Ferreira, Cristian Millán, Ramiro Ruiz, Alberto Junior, Bruno Fernandes
Affinity Workshop
Mon 10:45 Minimum-Delay Adaptation in Non-Stationary Reinforcement Learning via Online High-Confidence Change-Point Detection
Lucas Alegre, Ana Lucia Cetertich Bazzan , Bruno C. da Silva
Tutorial
Mon 12:00 Random Matrix Theory and ML (RMT+ML)
Fabian Pedregosa, Courtney Paquette, Thomas Trogdon, Jeffrey Pennington
Tutorial
Mon 13:30 Analysis of numerical algorithms
Thomas Trogdon
Affinity Workshop
Mon 13:50 Community pooling: LDA topic modeling in Twitter
Federico Albanese
Affinity Workshop
Mon 15:15 A Tree-Adaptation Mechanism for Covariate and Concept Drift
Leno Silva, Renato Vicente
Affinity Workshop
Mon 15:20 GAN-based Data Mapping for Model Adaptation
Leno Silva, Ruben Glatt, Renato Vicente
Mon 17:00 LatinX in AI Social
Maria Luisa Santiago, Miguel Alonso Jr, William Berrios
Oral
Tue 5:00 Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro
Oral
Tue 5:00 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen
Oral
Tue 5:00 Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar Duenez-Guzman, Sasha Vezhnevets, John Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
Oral
Tue 5:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Oral
Tue 5:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
Spotlight
Tue 5:20 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
Spotlight
Tue 5:20 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Spotlight
Tue 5:20 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Spotlight
Tue 5:20 Outlier-Robust Optimal Transport
Debarghya Mukherjee, Aritra Guha, Justin Solomon, Yuekai Sun, Mikhail Yurochkin
Spotlight
Tue 5:20 Consistent Nonparametric Methods for Network Assisted Covariate Estimation
Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar
Spotlight
Tue 5:20 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Spotlight
Tue 5:20 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Spotlight
Tue 5:25 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
Spotlight
Tue 5:25 A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang
Spotlight
Tue 5:25 A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How
Spotlight
Tue 5:25 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
Spotlight
Tue 5:25 Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung
Spotlight
Tue 5:25 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Spotlight
Tue 5:30 Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren R West, David C Hooper, Eric Horvitz, Erica Shenoy, John Guttag
Spotlight
Tue 5:30 Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine
Spotlight
Tue 5:30 Sliced Iterative Normalizing Flows
Biwei Dai, Uros Seljak
Spotlight
Tue 5:35 Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction
Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino
Spotlight
Tue 5:35 From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai, Ethan Fetaya, eli meirom, Gal Chechik, Haggai Maron
Spotlight
Tue 5:35 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Spotlight
Tue 5:40 Interpretable Stability Bounds for Spectral Graph Filters
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Spotlight
Tue 5:40 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Spotlight
Tue 5:40 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
Spotlight
Tue 5:40 Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty
Spotlight
Tue 5:45 Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks
Ciwan Ceylan, Salla Franzén, Florian T. Pokorny
Spotlight
Tue 5:45 Making transport more robust and interpretable by moving data through a small number of anchor points
Chi-Heng Lin, Mehdi Azabou, Eva Dyer
Spotlight
Tue 5:45 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng
Oral
Tue 6:00 Neural Architecture Search without Training
Joe Mellor, Jack Turner, Amos Storkey, Elliot Crowley
Oral Session
Tue 6:00 Deep Learning Algorithms 2
Oral
Tue 6:00 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
Tom Fei, Zhuoran Yang, Zhaoran Wang
Oral Session
Tue 6:00 Deep Learning Algorithms 1
Spotlight
Tue 6:20 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Spotlight
Tue 6:20 Projection Robust Wasserstein Barycenters
Minhui Huang, Shiqian Ma, Lifeng Lai
Spotlight
Tue 6:20 Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zhang Zihan, Yuan Zhou, Xiangyang Ji
Spotlight
Tue 6:20 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Spotlight
Tue 6:20 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang, Yun-Yun Tsai, Pin-Yu Chen
Spotlight
Tue 6:25 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Spotlight
Tue 6:30 Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Spotlight
Tue 6:30 How Framelets Enhance Graph Neural Networks
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Lió, Ming Li, Guido Montufar
Spotlight
Tue 6:35 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Spotlight
Tue 6:35 Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
Spotlight
Tue 6:35 Federated Continual Learning with Weighted Inter-client Transfer
Jaehong Yoon, Wonyong Jeong, GiWoong Lee, Eunho Yang, Sung Ju Hwang
Spotlight
Tue 6:35 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Spotlight
Tue 6:40 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Lió, Michael Bronstein
Spotlight
Tue 6:40 One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
Spotlight
Tue 6:40 Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley A Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N Kraemer
Spotlight
Tue 6:40 A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, wenjie liu, Nikolaos Freris, Hu Ding
Spotlight
Tue 6:45 Federated Learning of User Verification Models Without Sharing Embeddings
Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph B Soriaga, Max Welling
Spotlight
Tue 6:45 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
Spotlight
Tue 6:45 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Klicpera, Marten Lienen, Stephan Günnemann
Spotlight
Tue 6:45 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Oral
Tue 7:00 OmniNet: Omnidirectional Representations from Transformers
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Don Metzler
Oral Session
Tue 7:00 Deep Learning Algorithms 4
Oral Session
Tue 7:00 Deep Learning Algorithms 3
Oral
Tue 7:00 ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Wonjae Kim, Bokyung Son, Ildoo Kim
Oral
Tue 7:00 Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
Vien Mai, Mikael Johansson
Oral
Tue 7:00 World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang, Ge Yang, Bradly Stadie
Spotlight
Tue 7:20 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Spotlight
Tue 7:20 Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal Shlapentokh-Rothman
Spotlight
Tue 7:20 Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Spotlight
Tue 7:20 Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Obando Ceron, Pablo Samuel Castro
Spotlight
Tue 7:25 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Spotlight
Tue 7:25 Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn
Spotlight
Tue 7:25 GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang
Spotlight
Tue 7:30 Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz, Ismail Elezi, Laura Leal-Taixé
Spotlight
Tue 7:35 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Spotlight
Tue 7:40 Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney
Spotlight
Tue 7:40 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Spotlight
Tue 7:40 Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan, Mohit Bansal
Spotlight
Tue 7:45 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Spotlight
Tue 7:45 DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Babis Tsourakakis
Spotlight
Tue 7:45 Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface
Baorui Ma, Zhizhong Han, Yushen Liu, Matthias Zwicker
Poster
Tue 9:00 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Poster
Tue 9:00 Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro
Poster
Tue 9:00 Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney
Poster
Tue 9:00 Counterfactual Credit Assignment in Model-Free Reinforcement Learning
Thomas Mesnard, Theo Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Remi Munos
Poster
Tue 9:00 Sliced Iterative Normalizing Flows
Biwei Dai, Uros Seljak
Poster
Tue 9:00 Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
Poster
Tue 9:00 A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang
Poster
Tue 9:00 Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty
Poster
Tue 9:00 Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface
Baorui Ma, Zhizhong Han, Yushen Liu, Matthias Zwicker
Poster
Tue 9:00 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Poster
Tue 9:00 Consistent Nonparametric Methods for Network Assisted Covariate Estimation
Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar
Poster
Tue 9:00 Learning Intra-Batch Connections for Deep Metric Learning
Jenny Seidenschwarz, Ismail Elezi, Laura Leal-Taixé
Poster
Tue 9:00 Outlier-Robust Optimal Transport
Debarghya Mukherjee, Aritra Guha, Justin Solomon, Yuekai Sun, Mikhail Yurochkin
Poster
Tue 9:00 Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research
Johan Obando Ceron, Pablo Samuel Castro
Poster
Tue 9:00 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang, Yun-Yun Tsai, Pin-Yu Chen
Poster
Tue 9:00 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Poster
Tue 9:00 Federated Continual Learning with Weighted Inter-client Transfer
Jaehong Yoon, Wonyong Jeong, GiWoong Lee, Eunho Yang, Sung Ju Hwang
Poster
Tue 9:00 A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, wenjie liu, Nikolaos Freris, Hu Ding
Poster
Tue 9:00 Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Poster
Tue 9:00 UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
Tarun Gupta, Anuj Mahajan, Bei Peng, Wendelin Boehmer, Shimon Whiteson
Poster
Tue 9:00 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Poster
Tue 9:00 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
Poster
Tue 9:00 DeepWalking Backwards: From Embeddings Back to Graphs
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Babis Tsourakakis
Poster
Tue 9:00 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
Poster
Tue 9:00 How Framelets Enhance Graph Neural Networks
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Lió, Ming Li, Guido Montufar
Poster
Tue 9:00 ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Wonjae Kim, Bokyung Son, Ildoo Kim
Poster
Tue 9:00 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Poster
Tue 9:00 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Poster
Tue 9:00 Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Heroux, Benoit Gauzere, Pascal Vasseur, Sebastien Adam, Paul Honeine
Poster
Tue 9:00 Learning Routines for Effective Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
Poster
Tue 9:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Poster
Tue 9:00 Diversity Actor-Critic: Sample-Aware Entropy Regularization for Sample-Efficient Exploration
Seungyul Han, Youngchul Sung
Poster
Tue 9:00 Risk-Sensitive Reinforcement Learning with Function Approximation: A Debiasing Approach
Tom Fei, Zhuoran Yang, Zhaoran Wang
Poster
Tue 9:00 Reinforcement Learning for Cost-Aware Markov Decision Processes
Wesley A Suttle, Kaiqing Zhang, Zhuoran Yang, Ji Liu, David N Kraemer
Poster
Tue 9:00 Federated Learning of User Verification Models Without Sharing Embeddings
Hossein Hosseini, Hyunsin Park, Sungrack Yun, Christos Louizos, Joseph B Soriaga, Max Welling
Poster
Tue 9:00 OmniNet: Omnidirectional Representations from Transformers
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Don Metzler
Poster
Tue 9:00 Model-Free Reinforcement Learning: from Clipped Pseudo-Regret to Sample Complexity
Zhang Zihan, Yuan Zhou, Xiangyang Ji
Poster
Tue 9:00 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
Poster
Tue 9:00 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Poster
Tue 9:00 Projection Robust Wasserstein Barycenters
Minhui Huang, Shiqian Ma, Lifeng Lai
Poster
Tue 9:00 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Poster
Tue 9:00 Neural Architecture Search without Training
Joe Mellor, Jack Turner, Amos Storkey, Elliot Crowley
Poster
Tue 9:00 From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai, Ethan Fetaya, eli meirom, Gal Chechik, Haggai Maron
Poster
Tue 9:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Poster
Tue 9:00 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Lió, Michael Bronstein
Poster
Tue 9:00 GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang
Poster
Tue 9:00 Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Anima Anandkumar
Poster
Tue 9:00 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Poster
Tue 9:00 Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren R West, David C Hooper, Eric Horvitz, Erica Shenoy, John Guttag
Poster
Tue 9:00 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Poster
Tue 9:00 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Poster
Tue 9:00 One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
Poster
Tue 9:00 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Klicpera, Marten Lienen, Stephan Günnemann
Poster
Tue 9:00 World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang, Ge Yang, Bradly Stadie
Poster
Tue 9:00 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Poster
Tue 9:00 Interpretable Stability Bounds for Spectral Graph Filters
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Poster
Tue 9:00 Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
Vien Mai, Mikael Johansson
Poster
Tue 9:00 A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Dong Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan How
Poster
Tue 9:00 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Poster
Tue 9:00 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng
Poster
Tue 9:00 Making transport more robust and interpretable by moving data through a small number of anchor points
Chi-Heng Lin, Mehdi Azabou, Eva Dyer
Poster
Tue 9:00 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
Poster
Tue 9:00 Deep Reinforcement Learning amidst Continual Structured Non-Stationarity
Annie Xie, James Harrison, Chelsea Finn
Poster
Tue 9:00 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Poster
Tue 9:00 Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks
Ciwan Ceylan, Salla Franzén, Florian T. Pokorny
Poster
Tue 9:00 Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction
Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino
Poster
Tue 9:00 Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot
Joel Z Leibo, Edgar Duenez-Guzman, Sasha Vezhnevets, John Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel
Poster
Tue 9:00 Unifying Vision-and-Language Tasks via Text Generation
Jaemin Cho, Jie Lei, Hao Tan, Mohit Bansal
Poster
Tue 9:00 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen
Poster
Tue 9:00 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Poster
Tue 9:00 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Poster
Tue 9:00 Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal Shlapentokh-Rothman
Poster
Tue 9:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
Oral Session
Tue 17:00 Deep Learning Algorithms 6
Oral Session
Tue 17:00 Optimization and Algorithms 1
Oral
Tue 17:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Oral
Tue 17:00 A Tale of Two Efficient and Informative Negative Sampling Distributions
Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava
Oral Session
Tue 17:00 Deep Learning Algorithms 5
Oral
Tue 17:00 CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
Spotlight
Tue 17:20 TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models
Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica
Spotlight
Tue 17:20 Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu
Spotlight
Tue 17:20 Instance Specific Approximations for Submodular Maximization
Eric Balkanski, Sharon Qian, Yaron Singer
Spotlight
Tue 17:20 Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang
Spotlight
Tue 17:25 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Spotlight
Tue 17:25 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Spotlight
Tue 17:25 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Spotlight
Tue 17:30 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Spotlight
Tue 17:30 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Spotlight
Tue 17:30 Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Spotlight
Tue 17:30 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
Spotlight
Tue 17:35 Concentric mixtures of Mallows models for top-$k$ rankings: sampling and identifiability
Fabien Collas, Ekhine IRUROZKI
Spotlight
Tue 17:35 Online Graph Dictionary Learning
Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty
Spotlight
Tue 17:35 Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen
Spotlight
Tue 17:35 Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus
Spotlight
Tue 17:40 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Spotlight
Tue 17:40 Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset
Ilan Price, Jared Tanner
Spotlight
Tue 17:40 Heterogeneity for the Win: One-Shot Federated Clustering
Don Kurian Dennis, Tian Li, Virginia Smith
Spotlight
Tue 17:40 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Spotlight
Tue 17:40 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Spotlight
Tue 17:45 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Spotlight
Tue 17:45 Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar
Spotlight
Tue 17:45 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Spotlight
Tue 18:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Mohammad Abbasnejad, Reza Haffari
Oral
Tue 18:00 Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Oral
Tue 18:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Oral
Tue 18:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Oral Session
Tue 18:00 Optimization and Algorithms 2
Oral
Tue 18:00 A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar
Oral
Tue 18:00 The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu
Oral Session
Tue 18:00 Deep Learning Algorithms and Applications
Oral Session
Tue 18:00 Algorithms 1
Spotlight
Tue 18:05 Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry
Spotlight
Tue 18:10 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne
Oral
Tue 18:15 Few-Shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Spotlight
Tue 18:20 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Josh M Susskind, Jian Zhang, Russ Salakhutdinov, Hanlin Goh
Spotlight
Tue 18:25 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Spotlight
Tue 18:25 From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments
Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu
Spotlight
Tue 18:25 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Spotlight
Tue 18:30 Learning and Planning in Average-Reward Markov Decision Processes
Yi Wan, Abhishek Naik, Richard Sutton
Spotlight
Tue 18:30 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Spotlight
Tue 18:35 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
Spotlight
Tue 18:35 A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai
Spotlight
Tue 18:35 Light RUMs
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins
Spotlight
Tue 18:40 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Robin Ru, Cong Lu, Michael A Osborne
Spotlight
Tue 18:40 Information Obfuscation of Graph Neural Networks
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoff Gordon, Stefanie Jegelka, Russ Salakhutdinov
Spotlight
Tue 18:40 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Spotlight
Tue 18:40 Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Yorgos Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser
Spotlight
Tue 18:40 Randomized Algorithms for Submodular Function Maximization with a $k$-System Constraint
Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang
Spotlight
Tue 18:40 Policy Gradient Bayesian Robust Optimization for Imitation Learning
Zaynah Javed, Daniel Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca Dragan, Ken Goldberg
Spotlight
Tue 18:45 Leveraging Language to Learn Program Abstractions and Search Heuristics
Catherine Wong, Kevin Ellis, Josh Tenenbaum, Jacob Andreas
Spotlight
Tue 18:45 Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin
Spotlight
Tue 18:45 Emphatic Algorithms for Deep Reinforcement Learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Oral Session
Tue 19:00 Deep Learning Algorithms 8
Oral
Tue 19:00 Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm
TaeHo Yoon, Ernest Ryu
Oral
Tue 19:00 Hyperparameter Selection for Imitation Learning
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Emmanuel Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Oral Session
Tue 19:00 Deep Learning Algorithms 7
Oral
Tue 19:00 Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Unnat Jain, Raymond Yeh, Alex Schwing
Oral
Tue 19:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
Spotlight
Tue 19:20 Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi
Spotlight
Tue 19:20 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Spotlight
Tue 19:20 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Spotlight
Tue 19:20 Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
Spotlight
Tue 19:20 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Spotlight
Tue 19:25 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Spotlight
Tue 19:25 A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu
Spotlight
Tue 19:25 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Spotlight
Tue 19:25 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Spotlight
Tue 19:25 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Spotlight
Tue 19:30 Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Taufik Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Spotlight
Tue 19:30 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Spotlight
Tue 19:30 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu
Spotlight
Tue 19:30 Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun
Spotlight
Tue 19:30 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Spotlight
Tue 19:30 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Spotlight
Tue 19:30 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
Spotlight
Tue 19:35 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Spotlight
Tue 19:35 Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang
Spotlight
Tue 19:35 Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger, James Foster
Spotlight
Tue 19:35 Moreau-Yosida $f$-divergences
Dávid Terjék
Spotlight
Tue 19:35 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin D Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
Spotlight
Tue 19:35 1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
Spotlight
Tue 19:40 Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul G. Krishnan, David Sontag
Spotlight
Tue 19:40 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Spotlight
Tue 19:40 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Spotlight
Tue 19:45 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Spotlight
Tue 19:45 Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Spotlight
Tue 19:45 Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith
Spotlight
Tue 19:45 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Leveraging Language to Learn Program Abstractions and Search Heuristics
Catherine Wong, Kevin Ellis, Josh Tenenbaum, Jacob Andreas
Poster
Tue 21:00 A Tale of Two Efficient and Informative Negative Sampling Distributions
Shabnam Daghaghi, Tharun Medini, Nicholas Meisburger, Beidi Chen, Mengnan Zhao, Anshumali Shrivastava
Poster
Tue 21:00 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Poster
Tue 21:00 1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
Poster
Tue 21:00 Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm
TaeHo Yoon, Ernest Ryu
Poster
Tue 21:00 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Poster
Tue 21:00 Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Yorgos Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser
Poster
Tue 21:00 Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang
Poster
Tue 21:00 Randomized Algorithms for Submodular Function Maximization with a $k$-System Constraint
Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang
Poster
Tue 21:00 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Poster
Tue 21:00 Policy Gradient Bayesian Robust Optimization for Imitation Learning
Zaynah Javed, Daniel Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca Dragan, Ken Goldberg
Poster
Tue 21:00 Online Graph Dictionary Learning
Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary, Marco Corneli, Nicolas Courty
Poster
Tue 21:00 Light RUMs
Flavio Chierichetti, Ravi Kumar, Andrew Tomkins
Poster
Tue 21:00 A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu
Poster
Tue 21:00 Concentric mixtures of Mallows models for top-$k$ rankings: sampling and identifiability
Fabien Collas, Ekhine IRUROZKI
Poster
Tue 21:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
Poster
Tue 21:00 Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry
Poster
Tue 21:00 Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Poster
Tue 21:00 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Poster
Tue 21:00 The Emergence of Individuality
Jiechuan Jiang, Zongqing Lu
Poster
Tue 21:00 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Poster
Tue 21:00 Safe Reinforcement Learning with Linear Function Approximation
Sanae Amani, Christos Thrampoulidis, Lin Yang
Poster
Tue 21:00 A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai
Poster
Tue 21:00 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Poster
Tue 21:00 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne
Poster
Tue 21:00 Moreau-Yosida $f$-divergences
Dávid Terjék
Poster
Tue 21:00 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Poster
Tue 21:00 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Poster
Tue 21:00 Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger, James Foster
Poster
Tue 21:00 MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li, Abhishek Gupta, Ashwin D Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
Poster
Tue 21:00 Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu, Unnat Jain, Raymond Yeh, Alex Schwing
Poster
Tue 21:00 A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar
Poster
Tue 21:00 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Poster
Tue 21:00 Learning and Planning in Average-Reward Markov Decision Processes
Yi Wan, Abhishek Naik, Richard Sutton
Poster
Tue 21:00 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Robin Ru, Cong Lu, Michael A Osborne
Poster
Tue 21:00 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Poster
Tue 21:00 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Poster
Tue 21:00 Recomposing the Reinforcement Learning Building Blocks with Hypernetworks
Elad Sarafian, Shai Keynan, Sarit Kraus
Poster
Tue 21:00 Convex Regularization in Monte-Carlo Tree Search
Tuan Q Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Poster
Tue 21:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Mohammad Abbasnejad, Reza Haffari
Poster
Tue 21:00 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Poster
Tue 21:00 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Poster
Tue 21:00 DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu
Poster
Tue 21:00 CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
Poster
Tue 21:00 Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Taufik Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Poster
Tue 21:00 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
Poster
Tue 21:00 Instance Specific Approximations for Submodular Maximization
Eric Balkanski, Sharon Qian, Yaron Singer
Poster
Tue 21:00 Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu
Poster
Tue 21:00 Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar
Poster
Tue 21:00 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Poster
Tue 21:00 From Local to Global Norm Emergence: Dissolving Self-reinforcing Substructures with Incremental Social Instruments
Yiwei Liu, Jiamou Liu, Kaibin Wan, Zhan Qin, Zijian Zhang, Bakhadyr Khoussainov, Liehuang Zhu
Poster
Tue 21:00 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Poster
Tue 21:00 Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun
Poster
Tue 21:00 Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Poster
Tue 21:00 Differentiable Sorting Networks for Scalable Sorting and Ranking Supervision
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen
Poster
Tue 21:00 Heterogeneity for the Win: One-Shot Federated Clustering
Don Kurian Dennis, Tian Li, Virginia Smith
Poster
Tue 21:00 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Poster
Tue 21:00 Information Obfuscation of Graph Neural Networks
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoff Gordon, Stefanie Jegelka, Russ Salakhutdinov
Poster
Tue 21:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Poster
Tue 21:00 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Poster
Tue 21:00 Hyperparameter Selection for Imitation Learning
Léonard Hussenot, Marcin Andrychowicz, Damien Vincent, Robert Dadashi, Anton Raichuk, Sabela Ramos, Nikola Momchev, Sertan Girgin, Raphael Marinier, Lukasz Stafiniak, Emmanuel Orsini, Olivier Bachem, Matthieu Geist, Olivier Pietquin
Poster
Tue 21:00 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Poster
Tue 21:00 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Poster
Tue 21:00 TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models
Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica
Poster
Tue 21:00 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Poster
Tue 21:00 Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi
Poster
Tue 21:00 On-Policy Deep Reinforcement Learning for the Average-Reward Criterion
Yiming Zhang, Keith Ross
Poster
Tue 21:00 Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin
Poster
Tue 21:00 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Josh M Susskind, Jian Zhang, Russ Salakhutdinov, Hanlin Goh
Poster
Tue 21:00 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu
Poster
Tue 21:00 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Poster
Tue 21:00 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Poster
Tue 21:00 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Poster
Tue 21:00 Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
Poster
Tue 21:00 Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset
Ilan Price, Jared Tanner
Poster
Tue 21:00 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Poster
Tue 21:00 Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Poster
Tue 21:00 Emphatic Algorithms for Deep Reinforcement Learning
Ray Jiang, Tom Zahavy, Zhongwen Xu, Adam White, Matteo Hessel, Charles Blundell, Hado van Hasselt
Poster
Tue 21:00 Revisiting Peng's Q($\lambda$) for Modern Reinforcement Learning
Tadashi Kozuno, Yunhao Tang, Mark Rowland, Remi Munos, Steven Kapturowski, Will Dabney, Michal Valko, Dave Abel
Poster
Tue 21:00 Few-Shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Poster
Tue 21:00 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith
Poster
Tue 21:00 From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization
Julien Perolat, Remi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro Ortega, Neil Burch, Thomas Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls
Poster
Tue 21:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Poster
Tue 21:00 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Oral
Wed 5:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Oral
Wed 5:00 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris Maddison
Oral
Wed 5:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Oral
Wed 5:00 Cross-domain Imitation from Observations
Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
Oral
Wed 5:00 When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
Spotlight
Wed 5:20 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Spotlight
Wed 5:20 SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Puru Kar, Manik Varma
Spotlight
Wed 5:20 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
Spotlight
Wed 5:20 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Spotlight
Wed 5:20 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Spotlight
Wed 5:25 SMG: A Shuffling Gradient-Based Method with Momentum
Trang Tran, Lam Nguyen, Quoc Tran-Dinh
Spotlight
Wed 5:25 Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio
Spotlight
Wed 5:25 Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
Ankit Singh Rawat, Aditya Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Xinnan Yu, Sashank Jakkam Reddi, Sanjiv Kumar
Spotlight
Wed 5:25 Kernel Continual Learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees Snoek
Spotlight
Wed 5:30 Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David Bruns-Smith
Spotlight
Wed 5:30 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Spotlight
Wed 5:30 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Spotlight
Wed 5:30 Estimating $\alpha$-Rank from A Few Entries with Low Rank Matrix Completion
Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang
Spotlight
Wed 5:35 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Spotlight
Wed 5:35 Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans
Spotlight
Wed 5:40 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Spotlight
Wed 5:40 Composing Normalizing Flows for Inverse Problems
Jay Whang, Erik Lindgren, Alex Dimakis
Spotlight
Wed 5:40 Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
Spotlight
Wed 5:45 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Spotlight
Wed 5:45 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
Spotlight
Wed 5:45 Nonparametric Hamiltonian Monte Carlo
Carol Mak, Fabian Zaiser, Luke Ong
Spotlight
Wed 5:45 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 5:45 Learning from History for Byzantine Robust Optimization
Praneeth Karimireddy, Lie He, Martin Jaggi
Spotlight
Wed 5:45 Spectral vertex sparsifiers and pair-wise spanners over distributed graphs
Chunjiang Zhu, Qinqing Liu, Jinbo Bi
Oral
Wed 6:00 Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson
Oral
Wed 6:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Oral Session
Wed 6:00 Algorithms and Applications
Oral
Wed 6:00 Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
Oral
Wed 6:00 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling
Ying Fan, Yifei Ming
Oral
Wed 6:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Oral Session
Wed 6:00 Optimization and Algorithms 3
Oral
Wed 6:00 Understanding Instance-Level Label Noise: Disparate Impacts and Treatments
Yang Liu
Spotlight
Wed 6:20 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Spotlight
Wed 6:20 Near-Optimal Confidence Sequences for Bounded Random Variables
Arun Kuchibhotla, Qinqing Zheng
Spotlight
Wed 6:20 Selecting Data Augmentation for Simulating Interventions
Max Ilse, Jakub Tomczak, Patrick Forré
Spotlight
Wed 6:20 Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt
Spotlight
Wed 6:25 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Spotlight
Wed 6:25 Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results
Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm
Spotlight
Wed 6:25 Training Data Subset Selection for Regression with Controlled Generalization Error
Durga S, Rishabh Lyer, Ganesh Ramakrishnan, Abir De
Spotlight
Wed 6:25 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
Spotlight
Wed 6:25 Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Spotlight
Wed 6:30 Learning to Price Against a Moving Target
Renato Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah
Spotlight
Wed 6:30 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Spotlight
Wed 6:30 Online A-Optimal Design and Active Linear Regression
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
Spotlight
Wed 6:35 Learning from Noisy Labels with No Change to the Training Process
Mingyuan Zhang, Jane Lee, Shivani Agarwal
Spotlight
Wed 6:35 Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss
jiali wang, He Chen, Rujun Jiang, Xudong Li, Zihao Li
Spotlight
Wed 6:35 Fairness and Bias in Online Selection
Jose Correa, Andres Cristi, Paul Duetting, Ashkan Norouzi-Fard
Spotlight
Wed 6:35 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
Spotlight
Wed 6:35 Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
Uthsav Chitra, Kimberly Ding, Jasper C.H. Lee, Benjamin Raphael
Spotlight
Wed 6:40 Approximate Group Fairness for Clustering
Bo Li, Lijun Li, Ankang Sun, Chenhao Wang, Yingfan Wang
Spotlight
Wed 6:40 What does LIME really see in images?
Damien Garreau, Dina Mardaoui
Spotlight
Wed 6:40 ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
Spotlight
Wed 6:40 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Spotlight
Wed 6:45 Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse
Spotlight
Wed 6:45 Distributed Nystr\"{o}m Kernel Learning with Communications
Rong Yin, Weiping Wang, Dan Meng
Spotlight
Wed 6:45 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Oral
Wed 7:00 Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay Chaudhari, Reinhard Heckel
Oral
Wed 7:00 Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David Mguni, Ying Wen, Jun Wang
Affinity Workshop
Wed 7:00 Invited Talk #1 - Evaluating approximate inference for BNNs
Yingzhen Li
Oral
Wed 7:00 High-dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
Oral
Wed 7:00 Kernel Stein Discrepancy Descent
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Oral
Wed 7:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Spotlight
Wed 7:05 Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki
Spotlight
Wed 7:10 Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani
Spotlight
Wed 7:20 Instance-Optimal Compressed Sensing via Posterior Sampling
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price
Oral
Wed 7:20 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Spotlight
Wed 7:20 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet
Spotlight
Wed 7:20 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Spotlight
Wed 7:20 Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen, Bernie Wang, Christopher De Sa, Dean Foster
Spotlight
Wed 7:25 Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Spotlight
Wed 7:25 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Spotlight
Wed 7:25 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Spotlight
Wed 7:30 Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Spotlight
Wed 7:30 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Spotlight
Wed 7:30 Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Spotlight
Wed 7:30 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Spotlight
Wed 7:30 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Spotlight
Wed 7:30 Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar
Spotlight
Wed 7:30 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Spotlight
Wed 7:35 Active Deep Probabilistic Subsampling
Hans van Gorp, Iris Huijben, Bastiaan Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
Spotlight
Wed 7:35 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
Spotlight
Wed 7:35 Best Model Identification: A Rested Bandit Formulation
Leonardo Cella, Massimiliano Pontil, Claudio Gentile
Spotlight
Wed 7:35 An exact solver for the Weston-Watkins SVM subproblem
Yutong Wang, Clay Scott
Spotlight
Wed 7:40 Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps
Renyi Chen, Molei Tao
Spotlight
Wed 7:40 No-regret Algorithms for Capturing Events in Poisson Point Processes
Mojmir Mutny, Andreas Krause
Spotlight
Wed 7:40 Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
Spotlight
Wed 7:40 Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
Spotlight
Wed 7:40 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Spotlight
Wed 7:45 Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou
Spotlight
Wed 7:45 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Spotlight
Wed 7:45 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Spotlight
Wed 7:45 Faster Kernel Matrix Algebra via Density Estimation
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Poster
Wed 9:00 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Poster
Wed 9:00 Faster Kernel Matrix Algebra via Density Estimation
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Poster
Wed 9:00 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
Poster
Wed 9:00 ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
Poster
Wed 9:00 On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Poster
Wed 9:00 Fairness and Bias in Online Selection
Jose Correa, Andres Cristi, Paul Duetting, Ashkan Norouzi-Fard
Poster
Wed 9:00 Approximate Group Fairness for Clustering
Bo Li, Lijun Li, Ankang Sun, Chenhao Wang, Yingfan Wang
Poster
Wed 9:00 When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
Poster
Wed 9:00 Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse
Poster
Wed 9:00 Nonparametric Hamiltonian Monte Carlo
Carol Mak, Fabian Zaiser, Luke Ong
Poster
Wed 9:00 SMG: A Shuffling Gradient-Based Method with Momentum
Trang Tran, Lam Nguyen, Quoc Tran-Dinh
Poster
Wed 9:00 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 Training Data Subset Selection for Regression with Controlled Generalization Error
Durga S, Rishabh Lyer, Ganesh Ramakrishnan, Abir De
Poster
Wed 9:00 Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
Anna-Kathrin Kopetzki, Bertrand Charpentier, Daniel Zügner, Sandhya Giri, Stephan Günnemann
Poster
Wed 9:00 SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Puru Kar, Manik Varma
Poster
Wed 9:00 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Poster
Wed 9:00 Instance-Optimal Compressed Sensing via Posterior Sampling
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price
Poster
Wed 9:00 Selecting Data Augmentation for Simulating Interventions
Max Ilse, Jakub Tomczak, Patrick Forré
Poster
Wed 9:00 Variance Reduced Training with Stratified Sampling for Forecasting Models
Yucheng Lu, Youngsuk Park, Lifan Chen, Bernie Wang, Christopher De Sa, Dean Foster
Poster
Wed 9:00 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Poster
Wed 9:00 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Poster
Wed 9:00 Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings
Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani
Poster
Wed 9:00 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Poster
Wed 9:00 Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
Ankit Singh Rawat, Aditya Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Xinnan Yu, Sashank Jakkam Reddi, Sanjiv Kumar
Poster
Wed 9:00 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Poster
Wed 9:00 Cross-domain Imitation from Observations
Dripta S. Raychaudhuri, Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
Poster
Wed 9:00 Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou
Poster
Wed 9:00 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
Junhyung Park, Uri Shalit, Bernhard Schölkopf, Krikamol Muandet
Poster
Wed 9:00 Model-Free and Model-Based Policy Evaluation when Causality is Uncertain
David Bruns-Smith
Poster
Wed 9:00 Continuous Coordination As a Realistic Scenario for Lifelong Learning
Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar
Poster
Wed 9:00 Spectral vertex sparsifiers and pair-wise spanners over distributed graphs
Chunjiang Zhu, Qinqing Liu, Jinbo Bi
Poster
Wed 9:00 Align, then memorise: the dynamics of learning with feedback alignment
Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt
Poster
Wed 9:00 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Poster
Wed 9:00 Model-based Reinforcement Learning for Continuous Control with Posterior Sampling
Ying Fan, Yifei Ming
Poster
Wed 9:00 An exact solver for the Weston-Watkins SVM subproblem
Yutong Wang, Clay Scott
Poster
Wed 9:00 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Poster
Wed 9:00 Path Planning using Neural A* Search
Ryo Yonetani, Tatsunori Taniai, Mohammadamin Barekatain, Mai Nishimura, Asako Kanezaki
Poster
Wed 9:00 Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
Uthsav Chitra, Kimberly Ding, Jasper C.H. Lee, Benjamin Raphael
Poster
Wed 9:00 Learning from History for Byzantine Robust Optimization
Praneeth Karimireddy, Lie He, Martin Jaggi
Poster
Wed 9:00 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Poster
Wed 9:00 Estimating $\alpha$-Rank from A Few Entries with Low Rank Matrix Completion
Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang
Poster
Wed 9:00 Kernel Continual Learning
Mohammad Mahdi Derakhshani, Xiantong Zhen, Ling Shao, Cees Snoek
Poster
Wed 9:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Poster
Wed 9:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 9:00 Learning to Price Against a Moving Target
Renato Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah
Poster
Wed 9:00 Connecting Optimal Ex-Ante Collusion in Teams to Extensive-Form Correlation: Faster Algorithms and Positive Complexity Results
Gabriele Farina, Andrea Celli, Nicola Gatti, Tuomas Sandholm
Poster
Wed 9:00 Near-Optimal Confidence Sequences for Bounded Random Variables
Arun Kuchibhotla, Qinqing Zheng
Poster
Wed 9:00 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
Poster
Wed 9:00 Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay Chaudhari, Reinhard Heckel
Poster
Wed 9:00 Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Poster
Wed 9:00 Risk Bounds and Rademacher Complexity in Batch Reinforcement Learning
Yaqi Duan, Chi Jin, Zhiyuan Li
Poster
Wed 9:00 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Poster
Wed 9:00 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Poster
Wed 9:00 Best Model Identification: A Rested Bandit Formulation
Leonardo Cella, Massimiliano Pontil, Claudio Gentile
Poster
Wed 9:00 Generalised Lipschitz Regularisation Equals Distributional Robustness
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Poster
Wed 9:00 Learning from Noisy Labels with No Change to the Training Process
Mingyuan Zhang, Jane Lee, Shivani Agarwal
Poster
Wed 9:00 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
Poster
Wed 9:00 Kernel Stein Discrepancy Descent
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Poster
Wed 9:00 Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation
Qian Zhang, Yilin Zheng, Jean Honorio
Poster
Wed 9:00 Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet
Poster
Wed 9:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Poster
Wed 9:00 Modelling Behavioural Diversity for Learning in Open-Ended Games
Nicolas Perez-Nieves, Yaodong Yang, Oliver Slumbers, David Mguni, Ying Wen, Jun Wang
Poster
Wed 9:00 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Poster
Wed 9:00 High-dimensional Experimental Design and Kernel Bandits
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
Poster
Wed 9:00 Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing
Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht
Poster
Wed 9:00 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Poster
Wed 9:00 Online A-Optimal Design and Active Linear Regression
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
Poster
Wed 9:00 Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps
Renyi Chen, Molei Tao
Poster
Wed 9:00 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Poster
Wed 9:00 Ensemble Bootstrapping for Q-Learning
Oren Peer, Chen Tessler, Nadav Merlis, Ron Meir
Poster
Wed 9:00 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
Poster
Wed 9:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Poster
Wed 9:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Poster
Wed 9:00 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Poster
Wed 9:00 Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet
Poster
Wed 9:00 Composing Normalizing Flows for Inverse Problems
Jay Whang, Erik Lindgren, Alex Dimakis
Poster
Wed 9:00 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Poster
Wed 9:00 Active Deep Probabilistic Subsampling
Hans van Gorp, Iris Huijben, Bastiaan Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
Poster
Wed 9:00 Understanding Instance-Level Label Noise: Disparate Impacts and Treatments
Yang Liu
Poster
Wed 9:00 Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson
Poster
Wed 9:00 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Poster
Wed 9:00 Reward Identification in Inverse Reinforcement Learning
Kuno Kim, Shivam Garg, Kiran Shiragur, Stefano Ermon
Poster
Wed 9:00 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Poster
Wed 9:00 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Poster
Wed 9:00 Elastic Graph Neural Networks
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang
Poster
Wed 9:00 Distributed Nystr\"{o}m Kernel Learning with Communications
Rong Yin, Weiping Wang, Dan Meng
Poster
Wed 9:00 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Poster
Wed 9:00 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris Maddison
Poster
Wed 9:00 No-regret Algorithms for Capturing Events in Poisson Point Processes
Mojmir Mutny, Andreas Krause
Poster
Wed 9:00 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Poster
Wed 9:00 Bayesian Optimistic Optimisation with Exponentially Decaying Regret
Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh
Poster
Wed 9:00 Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss
jiali wang, He Chen, Rujun Jiang, Xudong Li, Zihao Li
Poster
Wed 9:00 What does LIME really see in images?
Damien Garreau, Dina Mardaoui
Poster
Wed 9:00 Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi, Dale Schuurmans
Affinity Workshop
Wed 9:25 Breakout Session 2.5: Un-bookclub Algorithms of Oppression
Oral
Wed 17:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Oral
Wed 17:00 Online Unrelated Machine Load Balancing with Predictions Revisited
Shi Li, Jiayi Xian
Oral
Wed 17:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Oral
Wed 17:00 The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
Spotlight
Wed 17:20 Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
Spotlight
Wed 17:20 Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee
Spotlight
Wed 17:20 MOTS: Minimax Optimal Thompson Sampling
Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu
Spotlight
Wed 17:25 Heterogeneous Risk Minimization
Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen
Spotlight
Wed 17:25 Regularized Online Allocation Problems: Fairness and Beyond
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Spotlight
Wed 17:25 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Spotlight
Wed 17:25 Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
Spotlight
Wed 17:25 Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti
Spotlight
Wed 17:25 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Spotlight
Wed 17:30 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Spotlight
Wed 17:30 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
Spotlight
Wed 17:35 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Spotlight
Wed 17:35 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Spotlight
Wed 17:40 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Spotlight
Wed 17:40 Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil
Spotlight
Wed 17:40 DriftSurf: Stable-State / Reactive-State Learning under Concept Drift
Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phil Gibbons
Spotlight
Wed 17:40 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Spotlight
Wed 17:40 How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation
Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler
Spotlight
Wed 17:45 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Spotlight
Wed 17:45 Dynamic Balancing for Model Selection in Bandits and RL
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
Spotlight
Wed 17:45 Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Spotlight
Wed 17:45 Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
Oral
Wed 18:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Oral
Wed 18:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Oral
Wed 18:00 Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Oral
Wed 18:00 Conformal prediction interval for dynamic time-series
Chen Xu, Yao Xie
Oral
Wed 18:00 Discriminative Complementary-Label Learning with Weighted Loss
Yi Gao, Min-Ling Zhang
Oral
Wed 18:00 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph E Gonzalez
Spotlight
Wed 18:20 GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan, Abir De, Rishabh Lyer
Spotlight
Wed 18:20 Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
Spotlight
Wed 18:20 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Spotlight
Wed 18:20 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
Syama Sundar Yadav Rangapuram, Lucien Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
Spotlight
Wed 18:25 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Spotlight
Wed 18:25 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Spotlight
Wed 18:25 Segmenting Hybrid Trajectories using Latent ODEs
Ian Shi, Quaid Morris
Spotlight
Wed 18:30 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang
Spotlight
Wed 18:30 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, rendong Ying, Chao Ma, Peilin Liu
Spotlight
Wed 18:30 Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou
Spotlight
Wed 18:30 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Spotlight
Wed 18:30 Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Yuzhou Chen, Ignacio Segovia Dominguez, Yulia R Gel
Spotlight
Wed 18:30 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Spotlight
Wed 18:30 Provable Meta-Learning of Linear Representations
Nilesh Tripuraneni, Chi Jin, Michael Jordan
Spotlight
Wed 18:35 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Spotlight
Wed 18:35 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
Changhun Jo, Kangwook Lee
Spotlight
Wed 18:35 Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke van Hoof
Spotlight
Wed 18:35 Event Outlier Detection in Continuous Time
Siqi Liu, Milos Hauskrecht
Spotlight
Wed 18:35 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Spotlight
Wed 18:40 Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
Spotlight
Wed 18:40 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu
Spotlight
Wed 18:40 Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto
Spotlight
Wed 18:40 Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case
Liyu Chen, Haipeng Luo
Spotlight
Wed 18:45 Cumulants of Hawkes Processes are Robust to Observation Noise
William Trouleau, Jalal Etesami, Matt Grossglauser, Negar Kiyavash, Patrick Thiran
Spotlight
Wed 18:45 Pure Exploration and Regret Minimization in Matching Bandits
Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic
Spotlight
Wed 18:45 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Spotlight
Wed 18:45 Solving Inverse Problems with a Flow-based Noise Model
Jay Whang, Qi Lei, Alex Dimakis
Oral
Wed 19:00 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Spotlight
Wed 19:00 Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan, baoxin Li
Oral
Wed 19:00 Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari
Oral
Wed 19:00 RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates
Oral Session
Wed 19:00 Algorithms 2
Oral
Wed 19:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Oral
Wed 19:00 Multi-Dimensional Classification via Sparse Label Encoding
BINBIN JIA, Min-Ling Zhang
Oral
Wed 19:00 A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
Spotlight
Wed 19:05 Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji
Spotlight
Wed 19:15 More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi
Spotlight
Wed 19:20 Training Recurrent Neural Networks via Forward Propagation Through Time
Anil Kag, Venkatesh Saligrama
Oral
Wed 19:20 Latent Programmer: Discrete Latent Codes for Program Synthesis
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
Spotlight
Wed 19:25 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Spotlight
Wed 19:25 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Spotlight
Wed 19:25 On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu, Jongho Park, Theo Rekatsinas, Christos Tzamos
Spotlight
Wed 19:25 Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Spotlight
Wed 19:30 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Spotlight
Wed 19:30 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Spotlight
Wed 19:30 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Spotlight
Wed 19:30 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Spotlight
Wed 19:35 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Spotlight
Wed 19:35 Beyond $log^2(T)$ regret for decentralized bandits in matching markets
Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
Spotlight
Wed 19:35 Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Spotlight
Wed 19:35 Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
yue cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Spotlight
Wed 19:40 Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
Spotlight
Wed 19:40 LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou
Spotlight
Wed 19:40 Mandoline: Model Evaluation under Distribution Shift
Mayee Chen, Karan Goel, Nimit Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Re
Spotlight
Wed 19:40 Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis
Spotlight
Wed 19:45 Adapting to misspecification in contextual bandits with offline regression oracles
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
Spotlight
Wed 19:45 SpreadsheetCoder: Formula Prediction from Semi-structured Context
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
Spotlight
Wed 19:45 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Spotlight
Wed 19:45 A large-scale benchmark for few-shot program induction and synthesis
Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Josh Tenenbaum
Poster
Wed 21:00 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang
Poster
Wed 21:00 Segmenting Hybrid Trajectories using Latent ODEs
Ian Shi, Quaid Morris
Poster
Wed 21:00 Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Poster
Wed 21:00 SpreadsheetCoder: Formula Prediction from Semi-structured Context
Xinyun Chen, Petros Maniatis, Rishabh Singh, Charles Sutton, Hanjun Dai, Max Lin, Denny Zhou
Poster
Wed 21:00 Near-Optimal Linear Regression under Distribution Shift
Qi Lei, Wei Hu, Jason Lee
Poster
Wed 21:00 Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan, baoxin Li
Poster
Wed 21:00 Optimal Streaming Algorithms for Multi-Armed Bandits
Tianyuan Jin, Keke Huang, Jing Tang, Xiaokui Xiao
Poster
Wed 21:00 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Poster
Wed 21:00 Event Outlier Detection in Continuous Time
Siqi Liu, Milos Hauskrecht
Poster
Wed 21:00 Pure Exploration and Regret Minimization in Matching Bandits
Flore Sentenac, Jialin Yi, Clément Calauzènes, Vianney Perchet, Milan Vojnovic
Poster
Wed 21:00 Adapting to misspecification in contextual bandits with offline regression oracles
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
Poster
Wed 21:00 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Poster
Wed 21:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Poster
Wed 21:00 Multi-Receiver Online Bayesian Persuasion
Matteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola Gatti
Poster
Wed 21:00 Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Poster
Wed 21:00 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Poster
Wed 21:00 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Poster
Wed 21:00 Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou
Poster
Wed 21:00 On Perceptual Lossy Compression: The Cost of Perceptual Reconstruction and An Optimal Training Framework
Zeyu Yan, Fei Wen, rendong Ying, Chao Ma, Peilin Liu
Poster
Wed 21:00 Beyond $log^2(T)$ regret for decentralized bandits in matching markets
Soumya Basu, Karthik Abinav Sankararaman, Abishek Sankararaman
Poster
Wed 21:00 Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
Poster
Wed 21:00 Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits
Tianyuan Jin, Jing Tang, Pan Xu, Keke Huang, Xiaokui Xiao, Quanquan Gu
Poster
Wed 21:00 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Poster
Wed 21:00 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Poster
Wed 21:00 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Poster
Wed 21:00 Multi-Dimensional Classification via Sparse Label Encoding
BINBIN JIA, Min-Ling Zhang
Poster
Wed 21:00 Fold2Seq: A Joint Sequence(1D)-Fold(3D) Embedding-based Generative Model for Protein Design
yue cao, Payel Das, Vijil Chenthamarakshan, Pin-Yu Chen, Igor Melnyk, Yang Shen
Poster
Wed 21:00 Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Poster
Wed 21:00 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Poster
Wed 21:00 More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi
Poster
Wed 21:00 Discriminative Complementary-Label Learning with Weighted Loss
Yi Gao, Min-Ling Zhang
Poster
Wed 21:00 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Poster
Wed 21:00 On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu, Jongho Park, Theo Rekatsinas, Christos Tzamos
Poster
Wed 21:00 Robust Pure Exploration in Linear Bandits with Limited Budget
Ayya Alieva, Ashok Cutkosky, Abhimanyu Das
Poster
Wed 21:00 Latent Programmer: Discrete Latent Codes for Program Synthesis
Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer
Poster
Wed 21:00 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Poster
Wed 21:00 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Poster
Wed 21:00 DriftSurf: Stable-State / Reactive-State Learning under Concept Drift
Ashraf Tahmasbi, Ellango Jothimurugesan, Srikanta Tirthapura, Phil Gibbons
Poster
Wed 21:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Poster
Wed 21:00 Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
Poster
Wed 21:00 Training Recurrent Neural Networks via Forward Propagation Through Time
Anil Kag, Venkatesh Saligrama
Poster
Wed 21:00 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Poster
Wed 21:00 Deep Coherent Exploration for Continuous Control
Yijie Zhang, Herke van Hoof
Poster
Wed 21:00 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
Syama Sundar Yadav Rangapuram, Lucien Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
Poster
Wed 21:00 Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case
Liyu Chen, Haipeng Luo
Poster
Wed 21:00 A large-scale benchmark for few-shot program induction and synthesis
Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Josh Tenenbaum
Poster
Wed 21:00 RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates
Poster
Wed 21:00 MOTS: Minimax Optimal Thompson Sampling
Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu
Poster
Wed 21:00 Online Unrelated Machine Load Balancing with Predictions Revisited
Shi Li, Jiayi Xian
Poster
Wed 21:00 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Poster
Wed 21:00 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Poster
Wed 21:00 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Poster
Wed 21:00 Improved Regret Bound and Experience Replay in Regularized Policy Iteration
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari
Poster
Wed 21:00 The Symmetry between Arms and Knapsacks: A Primal-Dual Approach for Bandits with Knapsacks
Xiaocheng Li, Chunlin Sun, Yinyu Ye
Poster
Wed 21:00 Resource Allocation in Multi-armed Bandit Exploration: Overcoming Sublinear Scaling with Adaptive Parallelism
Brijen Thananjeyan, Kirthevasan Kandasamy, Ion Stoica, Michael Jordan, Ken Goldberg, Joseph E Gonzalez
Poster
Wed 21:00 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Poster
Wed 21:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Poster
Wed 21:00 Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
Poster
Wed 21:00 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Poster
Wed 21:00 Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality
Tengyu Xu, Zhuoran Yang, Zhaoran Wang, Yingbin LIANG
Poster
Wed 21:00 GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
Krishnateja Killamsetty, Durga S, Ganesh Ramakrishnan, Abir De, Rishabh Lyer
Poster
Wed 21:00 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Poster
Wed 21:00 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Poster
Wed 21:00 Solving Inverse Problems with a Flow-based Noise Model
Jay Whang, Qi Lei, Alex Dimakis
Poster
Wed 21:00 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information
Changhun Jo, Kangwook Lee
Poster
Wed 21:00 LEGO: Latent Execution-Guided Reasoning for Multi-Hop Question Answering on Knowledge Graphs
Hongyu Ren, Hanjun Dai, Bo Dai, Xinyun Chen, Michihiro Yasunaga, Haitian Sun, Dale Schuurmans, Jure Leskovec, Denny Zhou
Poster
Wed 21:00 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Poster
Wed 21:00 Model Performance Scaling with Multiple Data Sources
Tatsunori Hashimoto
Poster
Wed 21:00 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Poster
Wed 21:00 Heterogeneous Risk Minimization
Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen
Poster
Wed 21:00 Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Yuzhou Chen, Ignacio Segovia Dominguez, Yulia R Gel
Poster
Wed 21:00 A Precise Performance Analysis of Support Vector Regression
Houssem Sifaou, Abla Kammoun, Mohamed-Slim Alouini
Poster
Wed 21:00 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Poster
Wed 21:00 Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
Poster
Wed 21:00 Regularized Online Allocation Problems: Fairness and Beyond
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Poster
Wed 21:00 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Poster
Wed 21:00 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Poster
Wed 21:00 Conformal prediction interval for dynamic time-series
Chen Xu, Yao Xie
Poster
Wed 21:00 Provably Efficient Algorithms for Multi-Objective Competitive RL
Tiancheng Yu, Yi Tian, Jingzhao Zhang, Suvrit Sra
Poster
Wed 21:00 How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation
Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler
Poster
Wed 21:00 Provable Meta-Learning of Linear Representations
Nilesh Tripuraneni, Chi Jin, Michael Jordan
Poster
Wed 21:00 Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis
Poster
Wed 21:00 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
Poster
Wed 21:00 Cyclically Equivariant Neural Decoders for Cyclic Codes
Xiangyu Chen, Min Ye
Poster
Wed 21:00 Mandoline: Model Evaluation under Distribution Shift
Mayee Chen, Karan Goel, Nimit Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Re
Poster
Wed 21:00 Dynamic Balancing for Model Selection in Bandits and RL
Ashok Cutkosky, Christoph Dann, Abhimanyu Das, Claudio Gentile, Aldo Pacchiano, Manish Purohit
Poster
Wed 21:00 Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
Poster
Wed 21:00 Cumulants of Hawkes Processes are Robust to Observation Noise
William Trouleau, Jalal Etesami, Matt Grossglauser, Negar Kiyavash, Patrick Thiran
Poster
Wed 21:00 Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Yunwen Lei, Zhenhuan Yang, Tianbao Yang, Yiming Ying
Poster
Wed 21:00 Robust Unsupervised Learning via L-statistic Minimization
Andreas Maurer, Daniela Angela Parletta, Andrea Paudice, Massimiliano Pontil
Poster
Wed 21:00 Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji
Oral
Thu 5:00 Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun
Oral
Thu 5:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Oral
Thu 5:00 Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
Oral
Thu 5:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Spotlight
Thu 5:20 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Spotlight
Thu 5:20 Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures
Martijn Gösgens, Aleksei Tikhonov, Liudmila Prokhorenkova
Spotlight
Thu 5:20 Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Spotlight
Thu 5:20 Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
Masahiro Kato, Takeshi Teshima
Spotlight
Thu 5:25 Local Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
Spotlight
Thu 5:25 Putting the ``Learning" into Learning-Augmented Algorithms for Frequency Estimation
Elbert Du, Franklyn Wang, Michael Mitzenmacher
Spotlight
Thu 5:25 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
Spotlight
Thu 5:25 Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Spotlight
Thu 5:30 Fairness for Image Generation with Uncertain Sensitive Attributes
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price
Spotlight
Thu 5:30 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
Spotlight
Thu 5:30 Robust Testing and Estimation under Manipulation Attacks
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Spotlight
Thu 5:30 Parameterless Transductive Feature Re-representation for Few-Shot Learning
Wentao Cui, Yuhong Guo
Spotlight
Thu 5:30 Near-Optimal Algorithms for Explainable k-Medians and k-Means
Kostya Makarychev, Liren Shan
Spotlight
Thu 5:35 GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Matthias Fey, Jan Lenssen, Frank Weichert, Jure Leskovec
Spotlight
Thu 5:35 Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Spotlight
Thu 5:35 On the Convergence of Hamiltonian Monte Carlo with Stochastic Gradients
Difan Zou, Quanquan Gu
Spotlight
Thu 5:40 Memory Efficient Online Meta Learning
Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama
Spotlight
Thu 5:40 Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Zolna
Spotlight
Thu 5:40 Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Spotlight
Thu 5:40 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Spotlight
Thu 5:40 Neural Transformation Learning for Deep Anomaly Detection Beyond Images
Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
Spotlight
Thu 5:45 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Spotlight
Thu 5:45 Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Spotlight
Thu 5:45 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Spotlight
Thu 5:45 Directional Bias Amplification
Angelina Wang, Olga Russakovsky
Spotlight
Thu 5:45 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Spotlight
Thu 5:45 A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio Mayrink Verdun
Oral
Thu 6:00 Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva
Oral
Thu 6:00 Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Ross, Finale Doshi-Velez
Oral
Thu 6:00 Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, rong jin
Oral
Thu 6:00 Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama
Oral
Thu 6:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Oral Session
Thu 6:00 Applications and Algorithms
Oral
Thu 6:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Spotlight
Thu 6:20 Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza
Spotlight
Thu 6:20 On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise
Jie Shen
Spotlight
Thu 6:20 Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Spotlight
Thu 6:20 HAWQ-V3: Dyadic Neural Network Quantization
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholaminejad, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael Mahoney, EECS Kurt Keutzer
Spotlight
Thu 6:20 In-Database Regression in Input Sparsity Time
Rajesh Jayaram, Alireza Samadian, David Woodruff, Peng Ye
Spotlight
Thu 6:20 First-Order Methods for Wasserstein Distributionally Robust MDP
Julien Grand-Clement, Christian Kroer
Spotlight
Thu 6:25 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Spotlight
Thu 6:25 CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
Dani Kiyasseh, Tingting Zhu, David Clifton
Spotlight
Thu 6:25 Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
Spotlight
Thu 6:25 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
Spotlight
Thu 6:25 PAPRIKA: Private Online False Discovery Rate Control
Wanrong Zhang, Gautam Kamath, Rachel Cummings
Spotlight
Thu 6:25 Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Spotlight
Thu 6:30 Transfer-Based Semantic Anomaly Detection
Lucas Deecke, Lukas Ruff, Rob Vandermeulen, Hakan Bilen
Spotlight
Thu 6:30 Adaptive Sampling for Best Policy Identification in Markov Decision Processes
Aymen Al Marjani, Alexandre Proutiere
Spotlight
Thu 6:30 Query Complexity of Adversarial Attacks
Grzegorz Gluch, Rüdiger Urbanke
Spotlight
Thu 6:35 Active Covering
Heinrich Jiang, Afshin Rostamizadeh
Spotlight
Thu 6:35 Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Spotlight
Thu 6:35 Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein
Spotlight
Thu 6:35 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Spotlight
Thu 6:40 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Spotlight
Thu 6:40 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Spotlight
Thu 6:40 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Spotlight
Thu 6:40 Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Spotlight
Thu 6:40 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Spotlight
Thu 6:40 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian YGER, Masashi Sugiyama
Spotlight
Thu 6:45 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan
Spotlight
Thu 6:45 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Spotlight
Thu 6:45 Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron Wagner, Jayadev Acharya
Oral
Thu 7:00 Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang
Oral
Thu 7:00 DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs
Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines
Oral
Thu 7:00 Locally Private k-Means in One Round
Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Oral
Thu 7:00 CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li
Oral
Thu 7:00 Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
Spotlight
Thu 7:20 Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra, yann lecun, Stephane Deny
Spotlight
Thu 7:20 Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik
Spotlight
Thu 7:20 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Spotlight
Thu 7:20 Skew Orthogonal Convolutions
Sahil Singla, Soheil Feizi
Spotlight
Thu 7:25 Active Testing: Sample-Efficient Model Evaluation
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Thu 7:25 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Spotlight
Thu 7:25 Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
Mihaela Curmei, Sarah Dean, Benjamin Recht
Spotlight
Thu 7:25 Parallel tempering on optimized paths
Saif Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Côté
Spotlight
Thu 7:25 Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
Spotlight
Thu 7:25 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Spotlight
Thu 7:30 Differentially-Private Clustering of Easy Instances
Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia
Spotlight
Thu 7:30 Personalized Federated Learning using Hypernetworks
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik
Spotlight
Thu 7:30 Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama
Spotlight
Thu 7:30 Rissanen Data Analysis: Examining Dataset Characteristics via Description Length
Ethan Perez, Douwe Kiela, Kyunghyun Cho
Spotlight
Thu 7:30 Defense against backdoor attacks via robust covariance estimation
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
Spotlight
Thu 7:30 Oblivious Sketching for Logistic Regression
Alexander Munteanu, Simon Omlor, David Woodruff
Spotlight
Thu 7:30 Sparse Bayesian Learning via Stepwise Regression
Sebastian Ament, Carla Gomes
Spotlight
Thu 7:35 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Spotlight
Thu 7:35 Adversarial Purification with Score-based Generative Models
Jongmin Yoon, Sung Ju Hwang, Juho Lee
Spotlight
Thu 7:35 Inference for Network Regression Models with Community Structure
Mengjie Pan, Tyler Mccormick, Bailey Fosdick
Spotlight
Thu 7:35 SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova
Spotlight
Thu 7:40 Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Spotlight
Thu 7:40 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Spotlight
Thu 7:40 Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Spotlight
Thu 7:40 Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
Raghav Singal, George Michailidis, Hoiyi Ng
Spotlight
Thu 7:40 Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
Spotlight
Thu 7:45 Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Spotlight
Thu 7:45 On the difficulty of unbiased alpha divergence minimization
Tomas Geffner, Justin Domke
Spotlight
Thu 7:45 Fairness of Exposure in Stochastic Bandits
Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims
Spotlight
Thu 7:45 Learning a Universal Template for Few-shot Dataset Generalization
Eleni Triantafillou, Hugo Larochelle, Richard Zemel, Vincent Dumoulin
Spotlight
Thu 7:45 To be Robust or to be Fair: Towards Fairness in Adversarial Training
Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang
Poster
Thu 9:00 Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Poster
Thu 9:00 PAPRIKA: Private Online False Discovery Rate Control
Wanrong Zhang, Gautam Kamath, Rachel Cummings
Poster
Thu 9:00 Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures
Martijn Gösgens, Aleksei Tikhonov, Liudmila Prokhorenkova
Poster
Thu 9:00 CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
Dani Kiyasseh, Tingting Zhu, David Clifton
Poster
Thu 9:00 Locally Private k-Means in One Round
Alisa Chang, Badih Ghazi, Ravi Kumar, Pasin Manurangsi
Poster
Thu 9:00 Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein
Poster
Thu 9:00 Differentially-Private Clustering of Easy Instances
Edith Cohen, Haim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia
Poster
Thu 9:00 Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Zolna
Poster
Thu 9:00 Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
Poster
Thu 9:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Poster
Thu 9:00 Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation
Masahiro Kato, Takeshi Teshima
Poster
Thu 9:00 Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Poster
Thu 9:00 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Poster
Thu 9:00 In-Database Regression in Input Sparsity Time
Rajesh Jayaram, Alireza Samadian, David Woodruff, Peng Ye
Poster
Thu 9:00 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Poster
Thu 9:00 SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova
Poster
Thu 9:00 Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
Mihaela Curmei, Sarah Dean, Benjamin Recht
Poster
Thu 9:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Poster
Thu 9:00 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Poster
Thu 9:00 Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Poster
Thu 9:00 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Poster
Thu 9:00 First-Order Methods for Wasserstein Distributionally Robust MDP
Julien Grand-Clement, Christian Kroer
Poster
Thu 9:00 Differentially Private Quantiles
Jennifer Gillenwater, Matthew Joseph, Alex Kulesza
Poster
Thu 9:00 Fairness for Image Generation with Uncertain Sensitive Attributes
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price
Poster
Thu 9:00 Parallel tempering on optimized paths
Saif Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Côté
Poster
Thu 9:00 Defense against backdoor attacks via robust covariance estimation
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
Poster
Thu 9:00 On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise
Jie Shen
Poster
Thu 9:00 Local Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
Poster
Thu 9:00 Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Ross, Finale Doshi-Velez
Poster
Thu 9:00 Near-Optimal Algorithms for Explainable k-Medians and k-Means
Kostya Makarychev, Liren Shan
Poster
Thu 9:00 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Poster
Thu 9:00 DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs
Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines
Poster
Thu 9:00 Active Testing: Sample-Efficient Model Evaluation
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Thu 9:00 Query Complexity of Adversarial Attacks
Grzegorz Gluch, Rüdiger Urbanke
Poster
Thu 9:00 Differentially Private Query Release Through Adaptive Projection
Sergul Aydore, William Brown, Michael Kearns, Krishnaram Kenthapadi, Luca Melis, Aaron Roth, Ankit Siva
Poster
Thu 9:00 Robust Testing and Estimation under Manipulation Attacks
Jayadev Acharya, Ziteng Sun, Huanyu Zhang
Poster
Thu 9:00 A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio Mayrink Verdun
Poster
Thu 9:00 Fairness of Exposure in Stochastic Bandits
Lequn Wang, Yiwei Bai, Wen Sun, Thorsten Joachims
Poster
Thu 9:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Poster
Thu 9:00 Transfer-Based Semantic Anomaly Detection
Lucas Deecke, Lukas Ruff, Rob Vandermeulen, Hakan Bilen
Poster
Thu 9:00 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Poster
Thu 9:00 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian YGER, Masashi Sugiyama
Poster
Thu 9:00 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Poster
Thu 9:00 On the Convergence of Hamiltonian Monte Carlo with Stochastic Gradients
Difan Zou, Quanquan Gu
Poster
Thu 9:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Poster
Thu 9:00 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Poster
Thu 9:00 To be Robust or to be Fair: Towards Fairness in Adversarial Training
Han Xu, Xiaorui Liu, Yaxin Li, Anil Jain, Jiliang Tang
Poster
Thu 9:00 Adaptive Sampling for Best Policy Identification in Markov Decision Processes
Aymen Al Marjani, Alexandre Proutiere
Poster
Thu 9:00 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels
Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu
Poster
Thu 9:00 Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Poster
Thu 9:00 CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li
Poster
Thu 9:00 Skew Orthogonal Convolutions
Sahil Singla, Soheil Feizi
Poster
Thu 9:00 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Poster
Thu 9:00 Memory Efficient Online Meta Learning
Durmus Alp Emre Acar, Ruizhao Zhu, Venkatesh Saligrama
Poster
Thu 9:00 Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks
Nezihe Merve Gürel, Xiangyu Qi, Luka Rimanic, Ce Zhang, Bo Li
Poster
Thu 9:00 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan
Poster
Thu 9:00 Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang
Poster
Thu 9:00 Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
Poster
Thu 9:00 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
Poster
Thu 9:00 Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Poster
Thu 9:00 Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama
Poster
Thu 9:00 Inference for Network Regression Models with Community Structure
Mengjie Pan, Tyler Mccormick, Bailey Fosdick
Poster
Thu 9:00 Sparse Bayesian Learning via Stepwise Regression
Sebastian Ament, Carla Gomes
Poster
Thu 9:00 Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
Poster
Thu 9:00 Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron Wagner, Jayadev Acharya
Poster
Thu 9:00 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Poster
Thu 9:00 Active Covering
Heinrich Jiang, Afshin Rostamizadeh
Poster
Thu 9:00 Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Poster
Thu 9:00 Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Minzhe Guo, Yevgeniy Vorobeychik
Poster
Thu 9:00 Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
Raghav Singal, George Michailidis, Hoiyi Ng
Poster
Thu 9:00 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Poster
Thu 9:00 Parameterless Transductive Feature Re-representation for Few-Shot Learning
Wentao Cui, Yuhong Guo
Poster
Thu 9:00 Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Poster
Thu 9:00 HAWQ-V3: Dyadic Neural Network Quantization
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholaminejad, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael Mahoney, EECS Kurt Keutzer
Poster
Thu 9:00 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Poster
Thu 9:00 Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, rong jin
Poster
Thu 9:00 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Poster
Thu 9:00 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Poster
Thu 9:00 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Poster
Thu 9:00 A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
Poster
Thu 9:00 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Poster
Thu 9:00 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Poster
Thu 9:00 Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama
Poster
Thu 9:00 Oblivious Sketching for Logistic Regression
Alexander Munteanu, Simon Omlor, David Woodruff
Poster
Thu 9:00 Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama
Poster
Thu 9:00 Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra, yann lecun, Stephane Deny
Poster
Thu 9:00 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Poster
Thu 9:00 Neural Transformation Learning for Deep Anomaly Detection Beyond Images
Chen Qiu, Timo Pfrom