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 ]

730 Results

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 8:00 Talk 1
Eyal Ofek
Expo Talk Panel
Sun 8:00 Cool Moves: Decoupling physical motions and self-avatar motions in Virtual Reality
Eyal Ofek
Expo Workshop
Sun 17:10 PaddleCV: Rich and Practical CV Models from Industrial Practice
Chenxia Li
Expo Workshop
Sun 18:10 PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation
Tianyi Wu
Expo Workshop
Sun 19:00 Paddle Graph Learning and Its Applications
Zhengjie Huang
Expo Talk Panel
Sun 19:00 Graviti Open Datasets: A peek into the future of Open Data
Yunkai Cui, Jake Zhao
Expo Workshop
Sun 20:00 Generalizing from a few examples by PaddleFSL
Yaqing Wang
Tutorial
Mon 8:00 From ML research to ML products: A path towards building models with real-world impact
Reza Salimi-Khorshidi, Peyman Faratin
Tutorial
Mon 8:00 Responsible AI in Industry: Practical Challenges and Lessons Learned
Krishnaram Kenthapadi, Ben Packer, Mehrnoosh Sameki, Nashlie Sephus
Tutorial
Mon 8:00 Continual Learning with Deep Architectures
Vincenzo Lomonaco, Irina Rish
Affinity Workshop
Mon 9:15 OCDE: Odds Conditional Density Estimator
Alex Aki Okuno, Felipe Polo
Affinity Workshop
Mon 10:40 Spatial Attention Adapted to a LSTM Architecture with Frame Selection for Human Action Recognition in Videos
ciorozco Orozco, María Elena Buemi, Julio Jacobo Berlles
Affinity Workshop
Mon 10:50 Generalized linear tree: a flexible algorithm for predicting continuous variables
Alberto Rodrigues Ferreira, Alex Aki Okuno
Affinity Workshop
Mon 14:00 Aspect-based Sentiment Analysis using BERT with Disentangled Attention
Ricardo Marcacini
Tutorial
Mon 20:00 Self-Attention for Computer Vision
Aravind Srinivas, Prajit Ramachandran, Ashish Vaswani
Oral
Tue 5:00 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen
Oral Session
Tue 5:00 Deep Learning Applications
Oral
Tue 5:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
Spotlight
Tue 5:25 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
Spotlight
Tue 5:25 Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model
Christian Thygesen, Christian Skjødt Steenmans, Ahmad Salim Al-Sibahi, Lys Sanz Moreta, Anders Bundgård Sørensen, Thomas Hamelryck
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 5:35 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Spotlight
Tue 5:40 Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty
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
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
Oral
Tue 6:00 Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
Chaobing Song, Stephen Wright, Jelena Diakonikolas
Spotlight
Tue 6:20 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Spotlight
Tue 6:25 Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang
Spotlight
Tue 6:30 KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu SUN, Hongxia Yang
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 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Spotlight
Tue 6:35 A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
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 6:40 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 6:45 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Klicpera, Marten Lienen, Stephan Günnemann
Spotlight
Tue 6:45 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
Spotlight
Tue 6:45 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Spotlight
Tue 6:45 Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy, Sheheryar Zaidi
Oral
Tue 7:00 World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang, Ge Yang, Bradly Stadie
Oral
Tue 7:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Spotlight
Tue 7:25 GLSearch: Maximum Common Subgraph Detection via Learning to Search
Yunsheng Bai, Derek Xu, Yizhou Sun, Wei Wang
Spotlight
Tue 7:25 Variational Data Assimilation with a Learned Inverse Observation Operator
Thomas Frerix, Dmitrii Kochkov, Jamie Smith, Daniel Cremers, Michael Brenner, Stephan Hoyer
Spotlight
Tue 7:35 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
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 Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond
Dennis Wei
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 One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
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 Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
Poster
Tue 9:00 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Poster
Tue 9:00 Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond
Dennis Wei
Poster
Tue 9:00 KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu SUN, Hongxia Yang
Poster
Tue 9:00 World Model as a Graph: Learning Latent Landmarks for Planning
Lunjun Zhang, Ge Yang, Bradly Stadie
Poster
Tue 9:00 Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy, Sheheryar Zaidi
Poster
Tue 9:00 Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model
Christian Thygesen, Christian Skjødt Steenmans, Ahmad Salim Al-Sibahi, Lys Sanz Moreta, Anders Bundgård Sørensen, Thomas Hamelryck
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 Low-Rank Sinkhorn Factorization
Meyer Scetbon, Marco Cuturi, Gabriel Peyré
Poster
Tue 9:00 Unbalanced minibatch Optimal Transport; applications to Domain Adaptation
Kilian Fatras, Thibault Séjourné, Rémi Flamary, Nicolas Courty
Poster
Tue 9:00 MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer
Poster
Tue 9:00 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
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 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 Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang
Poster
Tue 9:00 Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song
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 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
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 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 Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
Chaobing Song, Stephen Wright, Jelena Diakonikolas
Poster
Tue 9:00 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
Poster
Tue 9:00 Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Poster
Tue 9:00 Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
Jiaojiao Fan, Amirhossein Taghvaei, Yongxin Chen
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 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Poster
Tue 9:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Poster
Tue 9:00 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
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 Variational Data Assimilation with a Learned Inverse Observation Operator
Thomas Frerix, Dmitrii Kochkov, Jamie Smith, Daniel Cremers, Michael Brenner, Stephan Hoyer
Poster
Tue 9:00 Simultaneous Similarity-based Self-Distillation for Deep Metric Learning
Karsten Roth, Timo Milbich, Bjorn Ommer, Joseph Paul Cohen, Marzyeh Ghassemi
Oral
Tue 17:00 A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Wilson
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
Spotlight
Tue 17:20 What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng
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 17:25 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Spotlight
Tue 17:25 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Spotlight
Tue 17:30 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Spotlight
Tue 17:35 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine
Spotlight
Tue 17:40 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Spotlight
Tue 17:40 Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
Dongchan Min, Dong Bok Lee, Eunho Yang, Sung Ju Hwang
Spotlight
Tue 17:40 Stochastic Iterative Graph Matching
Linfeng Liu, Michael Hughes, Soha Hassoun, Liping Liu
Spotlight
Tue 17:45 Poolingformer: Long Document Modeling with Pooling Attention
Hang ZHANG, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen
Spotlight
Tue 17:45 LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu
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
Oral
Tue 18:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Oral Session
Tue 18:00 Deep Learning Algorithms and Applications
Spotlight
Tue 18:20 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Spotlight
Tue 18:20 EfficientNetV2: Smaller Models and Faster Training
Mingxing Tan, Quoc Le
Spotlight
Tue 18:25 Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
Spotlight
Tue 18:25 Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss
Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, xiaopeng zhang, Qi Tian
Spotlight
Tue 18:25 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Spotlight
Tue 18:25 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Spotlight
Tue 18:30 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
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 Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
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 18:40 Information Obfuscation of Graph Neural Networks
Peiyuan Liao, Han Zhao, Keyulu Xu, Tommi Jaakkola, Geoff Gordon, Stefanie Jegelka, Russ Salakhutdinov
Spotlight
Tue 18:40 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 18:45 BASGD: Buffered Asynchronous SGD for Byzantine Learning
Yi-Rui Yang, Wu-Jun Li
Spotlight
Tue 19:20 What Makes for End-to-End Object Detection?
Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo
Spotlight
Tue 19:20 Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang
Spotlight
Tue 19:25 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Spotlight
Tue 19:25 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
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 Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, Shixiang Gu
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 Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun
Spotlight
Tue 19:30 Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
Radu Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx
Spotlight
Tue 19:35 Compositional Video Synthesis with Action Graphs
Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Prof. Darrell, Amir Globerson
Spotlight
Tue 19:40 Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul G. Krishnan, David Sontag
Spotlight
Tue 19:40 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Spotlight
Tue 19:45 On a Combination of Alternating Minimization and Nesterov's Momentum
Sergey Guminov, Pavel Dvurechenskii, Nazarii Tupitsa, Alexander Gasnikov
Spotlight
Tue 19:45 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Poster
Tue 21:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Poster
Tue 21:00 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
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 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 Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh Sontakke, Arash Mehrjou, Laurent Itti, Bernhard Schölkopf
Poster
Tue 21:00 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Poster
Tue 21:00 Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem, Vladlen Koltun
Poster
Tue 21:00 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
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 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine
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 A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Wilson
Poster
Tue 21:00 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Poster
Tue 21:00 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
Poster
Tue 21:00 Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation
Dongchan Min, Dong Bok Lee, Eunho Yang, Sung Ju Hwang
Poster
Tue 21:00 BASGD: Buffered Asynchronous SGD for Byzantine Learning
Yi-Rui Yang, Wu-Jun Li
Poster
Tue 21:00 Poolingformer: Long Document Modeling with Pooling Attention
Hang ZHANG, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Weizhu Chen
Poster
Tue 21:00 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Poster
Tue 21:00 Learning to Weight Imperfect Demonstrations
Yunke Wang, Chang Xu, Bo Du, Honglak Lee
Poster
Tue 21:00 LARNet: Lie Algebra Residual Network for Face Recognition
Xiaolong Yang, Xiaohong Jia, Dihong Gong, Dong-Ming Yan, Zhifeng Li, Wei Liu
Poster
Tue 21:00 EfficientNetV2: Smaller Models and Faster Training
Mingxing Tan, Quoc Le
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 What Makes for End-to-End Object Detection?
Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo
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 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
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 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Poster
Tue 21:00 Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
Radu Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx
Poster
Tue 21:00 Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
Poster
Tue 21:00 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
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 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 Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang
Poster
Tue 21:00 On a Combination of Alternating Minimization and Nesterov's Momentum
Sergey Guminov, Pavel Dvurechenskii, Nazarii Tupitsa, Alexander Gasnikov
Poster
Tue 21:00 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Poster
Tue 21:00 Stochastic Iterative Graph Matching
Linfeng Liu, Michael Hughes, Soha Hassoun, Liping Liu
Poster
Tue 21:00 Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss
Xue Yang, Junchi Yan, Qi Ming, Wentao Wang, xiaopeng zhang, Qi Tian
Poster
Tue 21:00 What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng
Poster
Tue 21:00 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
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 Compositional Video Synthesis with Action Graphs
Amir Bar, Roei Herzig, Xiaolong Wang, Anna Rohrbach, Gal Chechik, Prof. Darrell, Amir Globerson
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 Optimizing persistent homology based functions
Mathieu Carrière, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
Oral
Wed 5:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Spotlight
Wed 5:20 Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller
Spotlight
Wed 5:20 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
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 Generalization Bounds in the Presence of Outliers: a Median-of-Means Study
Pierre Laforgue, Guillaume Staerman, Stephan Clémençon
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 5:25 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
Spotlight
Wed 5:30 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Spotlight
Wed 5:30 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Spotlight
Wed 5:40 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
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 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 5:45 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
Oral Session
Wed 6:00 Algorithms and Applications
Spotlight
Wed 6:20 Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang
Spotlight
Wed 6:20 How could Neural Networks understand Programs?
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
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 ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations
Chris Cummins, Zacharias Fisches, Tal Ben-Nun, Torsten Hoefler, Michael O'Boyle, Hugh Leather
Spotlight
Wed 6:30 How Do Adam and Training Strategies Help BNNs Optimization
Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng
Spotlight
Wed 6:30 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
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 6:35 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
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 6:45 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
Oral Session
Wed 7:00 Applications (Bio) 1
Oral
Wed 7:00 Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations
Tim Kim, Thomas Luo, Jonathan Pillow, Carlos Brody
Spotlight
Wed 7:20 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Spotlight
Wed 7:20 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Spotlight
Wed 7:20 Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis
Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, alexander gimson, Mihaela van der Schaar
Spotlight
Wed 7:25 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif
Spotlight
Wed 7:25 Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan van Gemert
Spotlight
Wed 7:30 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Spotlight
Wed 7:30 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Spotlight
Wed 7:30 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Spotlight
Wed 7:30 Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Spotlight
Wed 7:30 SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao YANG, Ru-Yuan Zhang, Lida LI, Xiaohua Xie
Spotlight
Wed 7:35 Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction
Aditi Jha, Michael J. Morais, Jonathan Pillow
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 7:40 On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu
Spotlight
Wed 7:45 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Spotlight
Wed 7:45 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Spotlight
Wed 7:45 AGENT: A Benchmark for Core Psychological Reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Josh Tenenbaum, Tomer Ullman
Affinity Workshop
Wed 8:30 Machine Learning Applications in Animal Sciences
Ambreen Hamadani
Poster
Wed 9:00 Optimizing persistent homology based functions
Mathieu Carrière, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
Poster
Wed 9:00 Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang
Affinity Workshop
Wed 9:00 Invited Talk #2 - Towards fairness & robustness in machine learning for dermatology
Celia Cintas
Poster
Wed 9:00 Improved Confidence Bounds for the Linear Logistic Model and Applications to Bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, Houssam Nassif
Poster
Wed 9:00 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
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 Fast Algorithms for Stackelberg Prediction Game with Least Squares Loss
jiali wang, He Chen, Rujun Jiang, Xudong Li, Zihao Li
Poster
Wed 9:00 Homomorphic Sensing: Sparsity and Noise
Liangzu Peng, Boshi Wang, Manolis Tsakiris
Poster
Wed 9:00 How Do Adam and Training Strategies Help BNNs Optimization
Zechun Liu, Zhiqiang Shen, Shichao Li, Koen Helwegen, Dong Huang, Kwang-Ting Cheng
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 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 Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction
Aditi Jha, Michael J. Morais, Jonathan Pillow
Poster
Wed 9:00 Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
Arrasy Rahman, Niklas Hopner, Filippos Christianos, Stefano V. Albrecht
Poster
Wed 9:00 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Poster
Wed 9:00 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions
Tal Lancewicki, Shahar Segal, Tomer Koren, Yishay Mansour
Poster
Wed 9:00 Generalization Bounds in the Presence of Outliers: a Median-of-Means Study
Pierre Laforgue, Guillaume Staerman, Stephan Clémençon
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 ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations
Chris Cummins, Zacharias Fisches, Tal Ben-Nun, Torsten Hoefler, Michael O'Boyle, Hugh Leather
Poster
Wed 9:00 SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao YANG, Ru-Yuan Zhang, Lida LI, Xiaohua Xie
Poster
Wed 9:00 Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller
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 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Poster
Wed 9:00 Batch Value-function Approximation with Only Realizability
Tengyang Xie, Nan Jiang
Poster
Wed 9:00 How could Neural Networks understand Programs?
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
Poster
Wed 9:00 Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan van Gemert
Poster
Wed 9:00 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
Poster
Wed 9:00 Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations
Tim Kim, Thomas Luo, Jonathan Pillow, Carlos Brody
Poster
Wed 9:00 Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Poster
Wed 9:00 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
Poster
Wed 9:00 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
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 An Algorithm for Stochastic and Adversarial Bandits with Switching Costs
Chloé Rouyer, Yevgeny Seldin, Nicolò Cesa-Bianchi
Poster
Wed 9:00 Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis
Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, alexander gimson, Mihaela van der Schaar
Poster
Wed 9:00 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Poster
Wed 9:00 Parametric Graph for Unimodal Ranking Bandit
CamilleS GAUTHIER, Romaric Gaudel, Elisa Fromont, Boammani Aser Lompo
Poster
Wed 9:00 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
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 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
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 On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu
Poster
Wed 9:00 Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail, Stephan Clémençon, Yannick Guyonvarch, Nathan NOIRY
Poster
Wed 9:00 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Poster
Wed 9:00 Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
Poster
Wed 9:00 AGENT: A Benchmark for Core Psychological Reasoning
Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan, Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Josh Tenenbaum, Tomer Ullman
Affinity Workshop
Wed 9:25 Breakout Session 2.8: Decision-Making in Social Settings: Addressing Strategic Feedback Effects
Affinity Workshop
Wed 9:25 Breakout Session 2.2: Leveraging Open-Source Tools for Natural Language Processing
Affinity Workshop
Wed 16:25 Breakout Session 3.3: Connecting Novel Perspectives on GNNs: A Cross-Domain Overview
Affinity Workshop
Wed 16:25 Breakout Session 3.2: ML Applications in Big Code
Oral
Wed 17:00 Learning Optimal Auctions with Correlated Valuations from Samples
CHUNXUE YANG, Xiaohui Bei
Oral
Wed 17:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
Oral
Wed 17:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Spotlight
Wed 17:20 Dynamic Planning and Learning under Recovering Rewards
David Simchi-Levi, Zeyu Zheng, Feng Zhu
Spotlight
Wed 17:25 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Spotlight
Wed 17:25 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Spotlight
Wed 17:25 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
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 17:45 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Spotlight
Wed 17:45 Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems
Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour
Spotlight
Wed 18:20 Gaussian Process-Based Real-Time Learning for Safety Critical Applications
Armin Lederer, Alejandro Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche
Spotlight
Wed 18:20 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Spotlight
Wed 18:20 Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
Spotlight
Wed 18:25 A Sharp Analysis of Model-based Reinforcement Learning with Self-Play
Qinghua Liu, Tiancheng Yu, Yu Bai, Chi Jin
Affinity Workshop
Wed 18:25 Breakout Session 4.3: Safely navigating scalability-reliability trade-offs in ML methods
Spotlight
Wed 18:25 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
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 Improved Regret Bounds of Bilinear Bandits using Action Space Analysis
Kyoungseok Jang, Kwang-Sung Jun, Se-Young Yun, Wanmo Kang
Spotlight
Wed 18:35 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Spotlight
Wed 18:40 Relative Deviation Margin Bounds
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh
Spotlight
Wed 18:40 Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang
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
Oral Session
Wed 19:00 Applications (Bio) 2
Oral
Wed 19:00 Break-It-Fix-It: Unsupervised Learning for Program Repair
Michihiro Yasunaga, Percy Liang
Oral
Wed 19:00 Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru
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
Oral
Wed 19:00 Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
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 Applications 1
Oral Session
Wed 19:00 Applications 2
Spotlight
Wed 19:20 A Differentiable Point Process with Its Application to Spiking Neural Networks
Hiroshi Kajino
Spotlight
Wed 19:20 An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang
Spotlight
Wed 19:20 Policy Analysis using Synthetic Controls in Continuous-Time
Alexis Bellot, Mihaela van der Schaar
Spotlight
Wed 19:25 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Spotlight
Wed 19:25 Diffusion Source Identification on Networks with Statistical Confidence
Quinlan Dawkins, Tianxi Li, Haifeng Xu
Spotlight
Wed 19:25 MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer
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 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
Spotlight
Wed 19:30 HyperHyperNetwork for the Design of Antenna Arrays
Shahar Lutati, Lior Wolf
Spotlight
Wed 19:30 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Spotlight
Wed 19:30 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Spotlight
Wed 19:30 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Spotlight
Wed 19:30 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Spotlight
Wed 19:30 ACE: Explaining cluster from an adversarial perspective
Yang Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble
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 19:35 SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won
Spotlight
Wed 19:40 12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha
Spotlight
Wed 19:40 Model Distillation for Revenue Optimization: Interpretable Personalized Pricing
Max Biggs, Wei Sun, Markus Ettl
Spotlight
Wed 19:40 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Spotlight
Wed 19:45 Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, ByungIn Yoo, Jae-Joon Han
Spotlight
Wed 19:45 Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo
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
Poster
Wed 21:00 Dynamic Planning and Learning under Recovering Rewards
David Simchi-Levi, Zeyu Zheng, Feng Zhu
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 Analysis of stochastic Lanczos quadrature for spectrum approximation
Tyler Chen, Thomas Trogdon, Shashanka Ubaru
Poster
Wed 21:00 Learning Optimal Auctions with Correlated Valuations from Samples
CHUNXUE YANG, Xiaohui Bei
Poster
Wed 21:00 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Poster
Wed 21:00 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
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 Approximation Theory of Convolutional Architectures for Time Series Modelling
Haotian Jiang, Zhong Li, Qianxiao Li
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 An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming
Minkai Xu, Wujie Wang, Shitong Luo, Chence Shi, Yoshua Bengio, Rafael Gomez-Bombarelli, Jian Tang
Poster
Wed 21:00 Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
Poster
Wed 21:00 Towards Distraction-Robust Active Visual Tracking
Fangwei Zhong, Peng Sun, Wenhan Luo, Tingyun Yan, Yizhou Wang
Poster
Wed 21:00 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Poster
Wed 21:00 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
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 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 Model Distillation for Revenue Optimization: Interpretable Personalized Pricing
Max Biggs, Wei Sun, Markus Ettl
Poster
Wed 21:00 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Poster
Wed 21:00 12-Lead ECG Reconstruction via Koopman Operators
Tomer Golany, Kira Radinsky, Daniel Freedman, Saar Minha
Poster
Wed 21:00 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Poster
Wed 21:00 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL
Andrea Zanette
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 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
Poster
Wed 21:00 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Poster
Wed 21:00 Gaussian Process-Based Real-Time Learning for Safety Critical Applications
Armin Lederer, Alejandro Ordóñez Conejo, Korbinian Maier, Wenxin Xiao, Jonas Umlauft, Sandra Hirche
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 SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Chandra Das, Myounggyu Won
Poster
Wed 21:00 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Poster
Wed 21:00 Break-It-Fix-It: Unsupervised Learning for Program Repair
Michihiro Yasunaga, Percy Liang
Poster
Wed 21:00 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Poster
Wed 21:00 ACE: Explaining cluster from an adversarial perspective
Yang Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble
Poster
Wed 21:00 Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction
Hangrui Bi, Hengyi Wang, Chence Shi, Connor Coley, Jian Tang, Hongyu Guo
Poster
Wed 21:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Poster
Wed 21:00 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
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 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Poster
Wed 21:00 Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, ByungIn Yoo, Jae-Joon Han
Poster
Wed 21:00 HyperHyperNetwork for the Design of Antenna Arrays
Shahar Lutati, Lior Wolf
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 Learning Gradient Fields for Molecular Conformation Generation
Chence Shi, Shitong Luo, Minkai Xu, Jian Tang
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 A Differentiable Point Process with Its Application to Spiking Neural Networks
Hiroshi Kajino
Poster
Wed 21:00 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
Poster
Wed 21:00 Policy Analysis using Synthetic Controls in Continuous-Time
Alexis Bellot, Mihaela van der Schaar
Poster
Wed 21:00 Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Poster
Wed 21:00 Diffusion Source Identification on Networks with Statistical Confidence
Quinlan Dawkins, Tianxi Li, Haifeng Xu
Oral
Thu 5:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Oral
Thu 5:00 Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun
Oral
Thu 5:00 Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Oral
Thu 5:00 Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
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 Memory-Efficient Pipeline-Parallel DNN Training
Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia
Spotlight
Thu 5:25 Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Spotlight
Thu 5:25 Putting the ``Learning" into Learning-Augmented Algorithms for Frequency Estimation
Elbert Du, Franklyn Wang, Michael Mitzenmacher
Spotlight
Thu 5:30 Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola
Spotlight
Thu 5:35 Optimization Planning for 3D ConvNets
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei
Spotlight
Thu 5:35 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
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 5:45 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee
Spotlight
Thu 5:45 Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor
Oral
Thu 6:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Oral
Thu 6:00 Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, YINGCONG CHEN, Hao Wang, Dina Katabi
Oral
Thu 6:00 I-BERT: Integer-only BERT Quantization
Sehoon Kim, Amir Gholaminejad, Zhewei Yao, Michael Mahoney, EECS Kurt Keutzer
Oral Session
Thu 6:00 Applications and Algorithms
Oral Session
Thu 6:00 Applications (NLP) 1
Spotlight
Thu 6:20 SparseBERT: Rethinking the Importance Analysis in Self-attention
Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Kwok
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 6:25 Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Spotlight
Thu 6:30 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Spotlight
Thu 6:30 Privacy-Preserving Video Classification with Convolutional Neural Networks
Sikha Pentyala, Rafael Dowsley, Martine De Cock
Spotlight
Thu 6:30 Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov
Spotlight
Thu 6:30 Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
Spotlight
Thu 6:35 Streaming Bayesian Deep Tensor Factorization
Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
Spotlight
Thu 6:35 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
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 Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Spotlight
Thu 6:45 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Spotlight
Thu 6:45 TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev
Spotlight
Thu 6:45 Sharf: Shape-conditioned Radiance Fields from a Single View
Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari
Oral
Thu 7:00 Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea
Oral
Thu 7:00 Annealed Flow Transport Monte Carlo
Michael Arbel, Alexander Matthews, Arnaud Doucet
Oral
Thu 7:00 On Disentangled Representations Learned from Correlated Data
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
Oral Session
Thu 7:00 Applications (CV and NLP)
Spotlight
Thu 7:20 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Spotlight
Thu 7:20 Nonparametric Decomposition of Sparse Tensors
Conor Tillinghast, Shandian Zhe
Spotlight
Thu 7:20 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Spotlight
Thu 7:20 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Spotlight
Thu 7:25 Active Testing: Sample-Efficient Model Evaluation
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth
Spotlight
Thu 7:25 Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
zhaoyang zhang, Wenqi Shao, Jinwei Gu, Xiaogang Wang, Ping Luo
Spotlight
Thu 7:25 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Spotlight
Thu 7:25 Markpainting: Adversarial Machine Learning meets Inpainting
David G Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson
Spotlight
Thu 7:25 Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
Mihaela Curmei, Sarah Dean, Benjamin Recht
Spotlight
Thu 7:30 Rissanen Data Analysis: Examining Dataset Characteristics via Description Length
Ethan Perez, Douwe Kiela, Kyunghyun Cho
Spotlight
Thu 7:35 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Spotlight
Thu 7:35 Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu, Baoquan Chen
Spotlight
Thu 7:40 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Spotlight
Thu 7:45 Neural Feature Matching in Implicit 3D Representations
Yunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves
Spotlight
Thu 7:45 EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang
Poster
Thu 9:00 Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu, Baoquan Chen
Poster
Thu 9:00 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Poster
Thu 9:00 Differentiable Dynamic Quantization with Mixed Precision and Adaptive Resolution
zhaoyang zhang, Wenqi Shao, Jinwei Gu, Xiaogang Wang, Ping Luo
Poster
Thu 9:00 Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
Mihaela Curmei, Sarah Dean, Benjamin Recht
Poster
Thu 9:00 Memory-Efficient Pipeline-Parallel DNN Training
Deepak Narayanan, Amar Phanishayee, Kaiyu Shi, Xie Chen, Matei Zaharia
Poster
Thu 9:00 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
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 Detecting Rewards Deterioration in Episodic Reinforcement Learning
Ido Greenberg, Shie Mannor
Poster
Thu 9:00 Annealed Flow Transport Monte Carlo
Michael Arbel, Alexander Matthews, Arnaud Doucet
Poster
Thu 9:00 Self-Damaging Contrastive Learning
Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Poster
Thu 9:00 Privacy-Preserving Video Classification with Convolutional Neural Networks
Sikha Pentyala, Rafael Dowsley, Martine De Cock
Poster
Thu 9:00 I-BERT: Integer-only BERT Quantization
Sehoon Kim, Amir Gholaminejad, Zhewei Yao, Michael Mahoney, EECS Kurt Keutzer
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 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Poster
Thu 9:00 Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Adam Foster, Desi Ivanova, ILYAS MALIK, Tom Rainforth
Poster
Thu 9:00 Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Poster
Thu 9:00 Rissanen Data Analysis: Examining Dataset Characteristics via Description Length
Ethan Perez, Douwe Kiela, Kyunghyun Cho
Poster
Thu 9:00 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Poster
Thu 9:00 A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
Poster
Thu 9:00 Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, YINGCONG CHEN, Hao Wang, Dina Katabi
Poster
Thu 9:00 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Poster
Thu 9:00 Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
Poster
Thu 9:00 Local Algorithms for Finding Densely Connected Clusters
Peter Macgregor, He Sun
Poster
Thu 9:00 Modeling Hierarchical Structures with Continuous Recursive Neural Networks
Jishnu Ray Chowdhury, Cornelia Caragea
Poster
Thu 9:00 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Poster
Thu 9:00 Markpainting: Adversarial Machine Learning meets Inpainting
David G Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson
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 On Disentangled Representations Learned from Correlated Data
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
Poster
Thu 9:00 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
Poster
Thu 9:00 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Poster
Thu 9:00 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning
Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee
Poster
Thu 9:00 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Poster
Thu 9:00 Active Testing: Sample-Efficient Model Evaluation
Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth
Poster
Thu 9:00 Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Zolna
Poster
Thu 9:00 Sharf: Shape-conditioned Radiance Fields from a Single View
Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari
Poster
Thu 9:00 Streaming Bayesian Deep Tensor Factorization
Shikai Fang, Zheng Wang, Zhimeng Pan, Ji Liu, Shandian Zhe
Poster
Thu 9:00 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Poster
Thu 9:00 Learning to Generate Noise for Multi-Attack Robustness
Divyam Madaan, Jinwoo Shin, Sung Ju Hwang
Poster
Thu 9:00 Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech
Vadim Popov, Ivan Vovk, Vladimir Gogoryan, Tasnima Sadekova, Mikhail Kudinov
Poster
Thu 9:00 Neural Feature Matching in Implicit 3D Representations
Yunlu Chen, Basura Fernando, Hakan Bilen, Thomas Mensink, Efstratios Gavves
Poster
Thu 9:00 EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang
Poster
Thu 9:00 Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Poster
Thu 9:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Poster
Thu 9:00 Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal
Poster
Thu 9:00 Optimization Planning for 3D ConvNets
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei
Poster
Thu 9:00 Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
Poster
Thu 9:00 TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev
Poster
Thu 9:00 SparseBERT: Rethinking the Importance Analysis in Self-attention
Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Kwok
Poster
Thu 9:00 Putting the ``Learning" into Learning-Augmented Algorithms for Frequency Estimation
Elbert Du, Franklyn Wang, Michael Mitzenmacher
Poster
Thu 9:00 Nonparametric Decomposition of Sparse Tensors
Conor Tillinghast, Shandian Zhe
Poster
Thu 9:00 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Poster
Thu 9:00 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Poster
Thu 9:00 Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola
Oral Session
Thu 17:00 Applications (NLP) 2
Oral
Thu 17:00 Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics
Arkopal Dutt, Andrey Lokhov, Marc Vuffray, Sidhant Misra
Oral
Thu 17:00 Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation
Xiang Lin, Simeng Han, Shafiq Joty
Oral
Thu 17:00 Global Prosody Style Transfer Without Text Transcriptions
Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David Cox, Mark Hasegawa-Johnson
Oral Session
Thu 17:00 Applications 3
Spotlight
Thu 17:20 SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform
Yuhang He, Niki Trigoni, Andrew Markham
Spotlight
Thu 17:25 Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Spotlight
Thu 17:25 EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture
Chenfeng Miao, Liang Shuang, Zhengchen Liu, Chen Minchuan, Jun Ma, Shaojun Wang, Jing Xiao
Spotlight
Thu 17:25 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Spotlight
Thu 17:30 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Spotlight
Thu 17:30 Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang
Spotlight
Thu 17:30 Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
Jaehyeon Kim, Jungil Kong, Juhee Son
Spotlight
Thu 17:35 BASE Layers: Simplifying Training of Large, Sparse Models
Mike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer
Spotlight
Thu 17:35 Learning de-identified representations of prosody from raw audio
Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed
Spotlight
Thu 17:35 Lossless Compression of Efficient Private Local Randomizers
Vitaly Feldman, Kunal Talwar
Spotlight
Thu 17:40 STRODE: Stochastic Boundary Ordinary Differential Equation
Huang Hengguan, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
Spotlight
Thu 17:40 UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
Spotlight
Thu 17:45 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
Elias Chaibub Neto
Spotlight
Thu 17:45 You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
Zhanpeng Zeng, Yunyang Xiong, Sathya Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
Oral
Thu 18:00 Label Inference Attacks from Log-loss Scores
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Seyi Feyisetan, Nathanael Teissier
Oral Session
Thu 18:00 Applications (NLP) 3
Oral
Thu 18:00 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Oral
Thu 18:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Oral
Thu 18:00 WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
Oral
Thu 18:00 Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing
Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao
Oral
Thu 18:00 Calibrate Before Use: Improving Few-shot Performance of Language Models
Tony Z. Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh
Spotlight
Thu 18:20 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Spotlight
Thu 18:20 On-the-fly Rectification for Robust Large-Vocabulary Topic Inference
Moontae Lee, June Cho, Kun Dong, David Mimno, David Bindel
Spotlight
Thu 18:25 CountSketches, Feature Hashing and the Median of Three
Kasper Green Larsen, Rasmus Pagh, Jakub Tětek
Spotlight
Thu 18:30 Disentangling syntax and semantics in the brain with deep networks
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Spotlight
Thu 18:30 Single Pass Entrywise-Transformed Low Rank Approximation
Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David Woodruff
Spotlight
Thu 18:35 Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose Alvarez
Spotlight
Thu 18:40 Few-shot Language Coordination by Modeling Theory of Mind
Hao Zhu, Graham Neubig, Yonatan Bisk
Spotlight
Thu 18:40 Projection techniques to update the truncated SVD of evolving matrices with applications
Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, superman Horesh, Kenneth Clarkson
Spotlight
Thu 18:45 Monte Carlo Variational Auto-Encoders
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
Oral
Thu 19:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Oral Session
Thu 19:00 Applications (NLP) 4
Oral
Thu 19:00 Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
Oral
Thu 19:00 Additive Error Guarantees for Weighted Low Rank Approximation
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena
Oral
Thu 19:00 Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
Cunxiao Du, Zhaopeng Tu, Jing Jiang
Spotlight
Thu 19:05 Neural Tangent Generalization Attacks
Jimmy Yuan, Shan-Hung (Brandon) Wu
Spotlight
Thu 19:20 Differentially Private Densest Subgraph Detection
Dung Nguyen, Anil Vullikanti
Oral
Thu 19:20 Mixed Cross Entropy Loss for Neural Machine Translation
Haoran Li, Wei Lu
Spotlight
Thu 19:20 Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination
Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang
Spotlight
Thu 19:20 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
Spotlight
Thu 19:25 One Pass Late Fusion Multi-view Clustering
Xinwang Liu, Li Liu, Qing Liao, Siwei Wang, Yi Zhang, Wenxuan Tu, Chang Tang, Jiyuan Liu, En Zhu
Spotlight
Thu 19:25 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Spotlight
Thu 19:35 Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu
Spotlight
Thu 19:40 Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation
Renjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang
Spotlight
Thu 19:40 A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
Spotlight
Thu 19:45 Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey
Spotlight Session
Thu 20:30 Applications 4
Spotlight
Thu 20:30 Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang
Spotlight
Thu 20:30 BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
Spotlight
Thu 20:30 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Spotlight
Thu 20:30 Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Spotlight Session
Thu 20:30 Applications (NLP) 5
Spotlight
Thu 20:35 Budgeted Heterogeneous Treatment Effect Estimation
Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou
Spotlight
Thu 20:35 Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
Spotlight
Thu 20:35 Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Patrick Verga, Bhuwan Dhingra, Russ Salakhutdinov, William Cohen
Spotlight
Thu 20:35 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
Xingchen Ma, Matthew B Blaschko
Spotlight
Thu 20:35 Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard
Spotlight
Thu 20:40 Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha
Spotlight
Thu 20:40 A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting
Eli N. Weinstein, Debora Marks
Spotlight
Thu 20:40 Value-at-Risk Optimization with Gaussian Processes
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Spotlight
Thu 20:40 Recovering AES Keys with a Deep Cold Boot Attack
Itamar Zimerman, Eliya Nachmani, Lior Wolf
Spotlight
Thu 20:45 Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato
Spotlight
Thu 20:45 CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Rama Vedantam, Arthur Szlam, Max Nickel, Ari Morcos, Brenden Lake
Spotlight
Thu 20:50 Learn2Hop: Learned Optimization on Rough Landscapes
Amil Merchant, Luke Metz, Samuel Schoenholz, Ekin Dogus Cubuk
Poster
Thu 21:00 Straight to the Gradient: Learning to Use Novel Tokens for Neural Text Generation
Xiang Lin, Simeng Han, Shafiq Joty
Poster
Thu 21:00 Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation
Renjie Zheng, Junkun Chen, Mingbo Ma, Liang Huang
Poster
Thu 21:00 Neural Tangent Generalization Attacks
Jimmy Yuan, Shan-Hung (Brandon) Wu
Poster
Thu 21:00 Budgeted Heterogeneous Treatment Effect Estimation
Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou
Poster
Thu 21:00 One Pass Late Fusion Multi-view Clustering
Xinwang Liu, Li Liu, Qing Liao, Siwei Wang, Yi Zhang, Wenxuan Tu, Chang Tang, Jiyuan Liu, En Zhu
Poster
Thu 21:00 Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
Poster
Thu 21:00 Calibrate Before Use: Improving Few-shot Performance of Language Models
Tony Z. Zhao, Eric Wallace, Shi Feng, Dan Klein, Sameer Singh
Poster
Thu 21:00 Projection techniques to update the truncated SVD of evolving matrices with applications
Vasileios Kalantzis, Georgios Kollias, Shashanka Ubaru, Athanasios N. Nikolakopoulos, superman Horesh, Kenneth Clarkson
Poster
Thu 21:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Poster
Thu 21:00 WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
Poster
Thu 21:00 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Poster
Thu 21:00 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Poster
Thu 21:00 Additive Error Guarantees for Weighted Low Rank Approximation
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Maheshakya Wijewardena
Poster
Thu 21:00 Lossless Compression of Efficient Private Local Randomizers
Vitaly Feldman, Kunal Talwar
Poster
Thu 21:00 Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Patrick Verga, Bhuwan Dhingra, Russ Salakhutdinov, William Cohen
Poster
Thu 21:00 Label Inference Attacks from Log-loss Scores
Abhinav Aggarwal, Shiva Kasiviswanathan, Zekun Xu, Seyi Feyisetan, Nathanael Teissier
Poster
Thu 21:00 Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang
Poster
Thu 21:00 Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing
Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao
Poster
Thu 21:00 Global Prosody Style Transfer Without Text Transcriptions
Kaizhi Qian, Yang Zhang, Shiyu Chang, Jinjun Xiong, Chuang Gan, David Cox, Mark Hasegawa-Johnson
Poster
Thu 21:00 On-the-fly Rectification for Robust Large-Vocabulary Topic Inference
Moontae Lee, June Cho, Kun Dong, David Mimno, David Bindel
Poster
Thu 21:00 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
Xingchen Ma, Matthew B Blaschko
Poster
Thu 21:00 Recovering AES Keys with a Deep Cold Boot Attack
Itamar Zimerman, Eliya Nachmani, Lior Wolf
Poster
Thu 21:00 Few-shot Language Coordination by Modeling Theory of Mind
Hao Zhu, Graham Neubig, Yonatan Bisk
Poster
Thu 21:00 You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
Zhanpeng Zeng, Yunyang Xiong, Sathya Ravi, Shailesh Acharya, Glenn Fung, Vikas Singh
Poster
Thu 21:00 A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting
Eli N. Weinstein, Debora Marks
Poster
Thu 21:00 CountSketches, Feature Hashing and the Median of Three
Kasper Green Larsen, Rasmus Pagh, Jakub Tětek
Poster
Thu 21:00 Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey
Poster
Thu 21:00 UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
Poster
Thu 21:00 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
Elias Chaibub Neto
Poster
Thu 21:00 CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Rama Vedantam, Arthur Szlam, Max Nickel, Ari Morcos, Brenden Lake
Poster
Thu 21:00 Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul G. Krishnan, David Sontag
Poster
Thu 21:00 Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose Alvarez
Poster
Thu 21:00 Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Poster
Thu 21:00 Smooth $p$-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
Sloan Nietert, Ziv Goldfeld, Kengo Kato
Poster
Thu 21:00 Learn2Hop: Learned Optimization on Rough Landscapes
Amil Merchant, Luke Metz, Samuel Schoenholz, Ekin Dogus Cubuk
Poster
Thu 21:00 Optimal Thompson Sampling strategies for support-aware CVaR bandits
Dorian Baudry, Romain Gautron, Emilie Kaufmann, Odalric-Ambrym Maillard
Poster
Thu 21:00 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Poster
Thu 21:00 Disentangling syntax and semantics in the brain with deep networks
Charlotte Caucheteux, Alexandre Gramfort, Jean-Remi King
Poster
Thu 21:00 Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
Jaehyeon Kim, Jungil Kong, Juhee Son
Poster
Thu 21:00 Mixed Cross Entropy Loss for Neural Machine Translation
Haoran Li, Wei Lu
Poster
Thu 21:00 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Poster
Thu 21:00 BASE Layers: Simplifying Training of Large, Sparse Models
Mike Lewis, Shruti Bhosale, Tim Dettmers, Naman Goyal, Luke Zettlemoyer
Poster
Thu 21:00 Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination
Wenbo Zheng, Lan Yan, Chao Gou, Fei-Yue Wang
Poster
Thu 21:00 Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang
Poster
Thu 21:00 SoundDet: Polyphonic Moving Sound Event Detection and Localization from Raw Waveform
Yuhang He, Niki Trigoni, Andrew Markham
Poster
Thu 21:00 Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu
Poster
Thu 21:00 EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture
Chenfeng Miao, Liang Shuang, Zhengchen Liu, Chen Minchuan, Jun Ma, Shaojun Wang, Jing Xiao
Poster
Thu 21:00 Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
Cunxiao Du, Zhaopeng Tu, Jing Jiang
Poster
Thu 21:00 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Poster
Thu 21:00 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
Poster
Thu 21:00 Learning de-identified representations of prosody from raw audio
Jack Weston, Raphael Lenain, Udeepa Meepegama, Emil Fristed
Poster
Thu 21:00 Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach
Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha
Poster
Thu 21:00 Self-Improved Retrosynthetic Planning
Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
Poster
Thu 21:00 Value-at-Risk Optimization with Gaussian Processes
Quoc Phong Nguyen, Zhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet
Poster
Thu 21:00 Single Pass Entrywise-Transformed Low Rank Approximation
Yifei Jiang, Yi Li, Yiming Sun, Jiaxin Wang, David Woodruff
Poster
Thu 21:00 Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics
Arkopal Dutt, Andrey Lokhov, Marc Vuffray, Sidhant Misra
Poster
Thu 21:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Poster
Thu 21:00 BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Weizhu Chen, Dayiheng Liu, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
Poster
Thu 21:00 Monte Carlo Variational Auto-Encoders
Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
Poster
Thu 21:00 STRODE: Stochastic Boundary Ordinary Differential Equation
Huang Hengguan, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
Poster
Thu 21:00 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Poster
Thu 21:00 Differentially Private Densest Subgraph Detection
Dung Nguyen, Anil Vullikanti
Workshop
Fri 2:00 Challenges in Deploying and monitoring Machine Learning Systems
Alessandra Tosi, Nathan Korda, Michael A Osborne, Stephen Roberts, Andrei Paleyes, Fariba Yousefi
Workshop
Fri 3:30 Applications in the legal system
Jess Montgomery, Charles Brecque, Teresa Scantamburlo
Workshop
Fri 5:00 Theory and Foundation of Continual Learning
Thang Doan, Bogdan Mazoure, Amal Rannen Triki, Rahaf Aljundi, Vincenzo Lomonaco, Xu He, Arslan Chaudhry Chaudhry
Workshop
Fri 5:00 ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu
Workshop
Fri 5:00 Tackling Climate Change with Machine Learning
Hari Prasanna Das , Katarzyna Tokarska, Maria João Sousa, Meareg Hailemariam, David Rolnick, Xiaoxiang Zhu, Yoshua Bengio
Workshop
Fri 5:55 Human-AI Collaboration in Sequential Decision-Making
Besmira Nushi, Adish Singla, Sebastian Tschiatschek
Workshop
Fri 5:55 ICML Workshop on Representation Learning for Finance and E-Commerce Applications
Senthil Kumar, Sameena Shah, Joan Bruna, Tom Goldstein, Erik Mueller, Oleg Rokhlenko, Hongxia Yang, Jianpeng Xu, Oluwatobi O Olabiyi, Charese Smiley, Bayan Bruss, Saurabh H Nagrecha, Svitlana Vyetrenko
Workshop
Fri 6:00 Uncertainty and Robustness in Deep Learning
Balaji Lakshminarayanan, Dan Hendrycks, Sharon Li, Jasper Snoek, Silvia Chiappa, Sebastian Nowozin, Tom Dietterich
Workshop
Fri 6:00 Reinforcement Learning for Real Life
Yuxi Li, Minmin Chen, Omer Gottesman, Lihong Li, Zongqing Lu, Rupam Mahmood, Niranjani Prasad, Zhiwei (Tony) Qin, Csaba Szepesvari, Matthew Taylor
Workshop
Fri 6:30 Who is Responsible for Adversarial Defense?
Kishor Datta Gupta
Workshop
Fri 6:39 Towards Efficient Machine Unlearning via Incremental View Maintenance
Sebastian Schelter
Workshop
Fri 6:50 DuckDQ: Data Quality Assertions for Machine Learning Pipelines
Till Döhmen
Workshop
Fri 7:31 AutoML Adoption in ML Software
Koen van der Blom
Workshop
Fri 8:00 The Neglected Assumptions In Causal Inference
Niki Kilbertus, Lily Hu, Laura Balzer, Uri Shalit, Alexander D'Amour, Razieh Nabi
Workshop
Fri 8:00 Machine Learning for Data: Automated Creation, Privacy, Bias
Zhiting Hu Hu, Li Erran Li, Willie Neiswanger, Benedikt Boecking, Yi Xu, Belinda Zeng
Workshop
Fri 8:30 Invited Talk 5: Applications of normalizing flows: semi-supervised learning, anomaly detection, and continual learning
Polina Kirichenko
Workshop
Fri 9:00 In Search of Effective and Reproducible Clinical Imaging Biomarkers for Pancreatic Oncology Applications of Screening, Diagnosis and Prognosis
Le Lu
Workshop
Fri 9:49 Neural Fixed-Point Acceleration for Convex Optimization
Shobha Venkataraman
Workshop
Fri 9:50 Model-less Inference Serving for ease-to-use and cost-efficiency
Neeraja J Yadwadkar
Workshop
Fri 12:30 Evaluating deep learning models with applications to NLP
Nazneen Rajani
Workshop
Fri 12:50 Paper Presentation 3: Dynamic Customer Embedding for Financial Service Applications
Sam Sharpe, Qianyu Cheng, Dwipam Katariya, Karthik Rajasethupathy
Workshop
Sat 4:45 A Blessing in Disguise: The Prospects and Perils of Adversarial Machine Learning
Hang Su, Yinpeng Dong, Tianyu Pang, Eric Wong, Zico Kolter, Shuo Feng, Bo Li, Henry Liu, Dan Hendrycks, Francesco Croce, Leslie Rice, Tian Tian
Workshop
Sat 5:40 Workshop on Socially Responsible Machine Learning
Chaowei Xiao, Animashree Anandkumar, Mingyan Liu, Dawn Song, Raquel Urtasun, Jieyu Zhao, Xueru Zhang, Cihang Xie, Xinyun Chen, Bo Li
Workshop
Sat 6:00 Subset Selection in Machine Learning: From Theory to Applications
Rishabh Lyer, Abir De, Ganesh Ramakrishnan, Jeff Bilmes
Workshop
Sat 7:00 Beyond first-order methods in machine learning systems
Albert S Berahas, Tasos Kyrillidis, Fred Roosta, Amir Gholaminejad, Michael Mahoney, Rachael Tappenden, Raghu Bollapragada, Rixon Crane, J. Lyle Kim
Workshop
Sat 7:00 Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning (ITR3)
Ahmad Beirami, Flavio Calmon, Berivan Isik, Haewon Jeong, Matthew Nokleby, Cynthia Rush
Workshop
Sat 7:00 Differentiable learning Under Algorithmic Triage
Manuel Gomez Rodriguez
Workshop
Sat 7:05 CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Workshop
Sat 7:10 Recent trends in regularization methods with adaptive accuracy requirements
Stefania Bellavia
Workshop
Sat 8:05 Conjugate gradient techniques for nonconvex optimization
Clément Royer
Workshop
Sat 8:45 Time Series Workshop
Yian Ma, Ehi Nosakhare, Yuyang Wang, Scott Yang, Rose Yu
Workshop
Sat 9:33 Nested Conformal Prediction Sets for Classification with Applications to Probation Data (Spotlight #3)
Richard Berk
Workshop
Sat 9:42 Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods (Spotlight #4)
Eyke Hüllermeier
Workshop
Sat 9:45 Mike West: Multiscale Bayesian Modelling: Ideas and Examples from Consumer Sales
Workshop
Sat 10:15 On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Sat 11:45 Morning Poster Session: Evolving-Graph Gaussian Processes
David Blanco-Mulero
Workshop
Sat 11:45 Morning Poster Session: PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
Paul Jeha, Pedro Mercado
Workshop
Sat 11:45 Morning Poster Session: Integrating LSTMs and GNNs for COVID-19 Forecasting
Nate J Sesti
Workshop
Sat 11:45 Morning Poster Session: Electric Load Forecasting with Boosting based Sample Transfer
Tracy Cui
Workshop
Sat 11:45 Morning Poster Session: JKOnet: Proximal Optimal Transport Modeling of Population Dynamics
Charlotte Bunne
Workshop
Sat 11:45 Morning Poster Session: Recurrent Intensity Modeling for User Recommendation and Online Matching
Yifei Ma
Workshop
Sat 12:04 Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
Sat 14:00 Data-efficient and Robust Learning from Massive Datasets
Baharan Mirzasoleiman
Workshop
Sat 15:15 Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
Yu Bai, Chi Jin, Huan Wang, Caiming Xiong
Workshop
Sat 15:30 Solving Multi-Arm Bandit Using a Few Bits of Communication
Osama Hanna, Lin Yang, Christina Fragouli
Workshop
Sat 15:55 Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Workshop
Sat 15:59 Improved Regret Bounds for Online Submodular Maximization
Omid Sadeghi, Maryam Fazel
Workshop
Sat 16:15 Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures (Spotlight #6)
Ben Kompa
Workshop
Sat 16:19 Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity
Praneeth Vepakomma, Ramesh Raskar
Workshop
AutoML Adoption in ML Software
Koen van der Blom, Alex Serban, Holger Hoos, Joost Visser
Workshop
Tree-based local explanations of machine learning model predictions – AraucanaXAI
Enea Parimbelli, Giovanna Nicora, Szymon Wilk, Wojtek Michalowski, Riccardo Bellazzi
Workshop
Solving inverse problems with deep neural networks driven by sparse signal decomposition in a physics-based dictionary
Gaetan Rensonnet
Workshop
Evaluating subgroup disparity using epistemic for breast density assessment in mammography
charlie lu, Andreanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer
Workshop
A reject option for automated sleep stage scoring
Dries Van der Plas, Wannes Meert, Jesse Davis
Workshop
Assessing Bias in Medical AI
Melanie Ganz, Sune Hannibal Holm, Aasa Feragen
Workshop
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Workshop
Machine Learning API Shift Assessments: Change is Coming!
Lingjiao Chen, James Zou, Matei Zaharia
Workshop
Improving Adversarial Robustness in 3D Point Cloud Classification via Self-Supervisions
Jiachen Sun, yulong cao, Christopher Choy, Zhiding Yu, Chaowei Xiao, Anima Anandkumar, Zhuoqing Morley Mao
Workshop
Towards a Unified Framework for Fair and Stable Graph Representation Learning
Chirag Agarwal, Hima Lakkaraju, Marinka Zitnik
Workshop
Do Humans Trust Advice More if it Comes from AI? An Analysis of Human-AI Interactions
Kailas Vodrahalli, James Zou
Workshop
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu, Tamer Basar
Workshop
Learning Adversarial Markov Decision Processes with Delayed Feedback
Tal Lancewicki, Aviv Rosenberg, Yishay Mansour
Workshop
Provable RL with Exogenous Distractors via Multistep Inverse Dynamics
Yonathan Efroni, Dipendra Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
Workshop
Provably efficient exploration-free transfer RL for near-deterministic latent dynamics
Yao Liu, Dipendra Misra, Miro Dudik, Robert Schapire
Workshop
Generalization of the Change of Variables Formula with Applications to Residual Flows
Niklas Koenen
Workshop
VoroCNN: Deep Convolutional Neural Network Built on 3D Voronoi Tessellation of Protein Structures
Ilia Igashov
Workshop
MultImp: Multiomics Generative Models for Data Imputation
Yining Jiao
Workshop
Statistical correction of input gradients for black box models trained with categorical input features
Antonio Majdandzic
Workshop
VEGN: variant effect prediction with graph neural network
Carolin Lawrence
Workshop
Deep neural networks identify sequence context features predictive of transcription factor binding
AN ZHENG
Workshop
APObind: A Dataset of Ligand Unbound Protein Conformations for Machine Learning Applications in De Novo Drug Design
Rishal Aggarwal
Workshop
Exploring the latent space of deep generative models: Applications to G-protein coupled receptors
Lood van Niekerk
Workshop
TCR-epitope binding affinity prediction using multi-head self attention model
Michael Cai
Workshop
Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
Ashly Lau, Jonathan Passerat-Palmbach
Workshop
Reinforcement Learning for (Mixed) Integer Programming: Smart Feasibility Pump
Mengxin Wang, Meng Qi, Zuo-Jun Shen
Workshop
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach
Haipeng Chen, Wei Qiu, Han-Ching Ou, Bo An, Milind Tambe
Workshop
On the Difficulty of Generalizing Reinforcement Learning Framework for Combinatorial Optimization
Mostafa Pashazadeh, Kui Wu
Workshop
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
Haruka Kiyohara, Yuta Saito, Tatsuya Matsuhiro, Yusuke Narita, Nobuyuki Shimizu, Yasuo Yamamoto
Workshop
Automatic Risk Adaptation in Distributional Reinforcement Learning
Frederik Schubert, Theresa Eimer, Bodo Rosenhahn, Marius Lindauer
Workshop
Reward-Free Attacks in Multi-Agent Reinforcement Learning
Ted Fujimoto, Timothy Doster, Adam Attarian, Jill Brandenberger, Nathan Hodas
Workshop
Optimization of high precision manufacturing by Monte Carlo Tree Search
Dorina Weichert, Alexander Kister
Workshop
AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning
Maayan Shvo, Zhiming Hu, Rodrigo A Toro Icarte, Iqbal Mohomed, Allan Jepson, Sheila McIlraith
Workshop
Avoiding Overfitting to the Importance Weights in Offline Policy Optimization
Yao Liu, Emma Brunskill
Workshop
Is Bang-Bang Control All You Need?
Tim Seyde, Igor Gilitschenski, Wilko Schwarting, Bartolomeo Stellato, Martin Riedmiller, Markus Wulfmeier, Daniela Rus
Workshop
Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces
Athina Nisioti, Dario Pavllo, Jonas Kohler
Workshop
Constraints Penalized Q-Learning for Safe Offline Reinforcement Learning
Haoran Xu, Xianyuan Zhan, Xiangyu Zhu
Workshop
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta, Justin Yu, Tony Z. Zhao, Vikash Kumar, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine
Workshop
A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning
Tianchi Cai, Wenpeng Zhang, Lihong Gu, Xiaodong Zeng, Jinjie Gu
Workshop
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images
Weina Jin, Xiaoxiao Li, Ghassan Hamarneh
Affinity Workshop
Can You Explain That, Better? Comprehensible Text Analytics for SE Applications
Quang Huy Tu, Arjun Subramonian
Workshop
VICAUSE: Simultaneous missing value imputation and causal discovery
Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Pyton Jones, Miltiadis Allamanis, Cheng Zhang
Workshop
Solving Multi-Arm Bandit Using a Few Bits of Communication
Osama Hanna, Lin Yang, Christina Fragouli
Workshop
On the Theory of Reinforcement Learning with Once-per-Episode Feedback
Niladri Chatterji, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Workshop
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
Yu Bai, Chi Jin, Huan Wang, Caiming Xiong
Workshop
IADA: Iterative Adversarial Data Augmentation Using Formal Verification and Expert Guidance
Ruixuan Liu, Changliu Liu
Workshop
Differentiable Learning Under Triage
Nastaran Okati, Abir De, Manuel Gomez Rodriguez
Workshop
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke, Fabrizio Silvestri
Workshop
Personalizing Pretrained Models
Mina Khan, Advait Rane, Pattie Maes
Workshop
Data-Efficient Exploration with Self Play for Atari
Michael Laskin, Catherine Cang, Ryan Rudes, Pieter Abbeel
Workshop
Adversarial Interaction Attacks: Fooling AI to Misinterpret Human Intentions
Nodens Koren, Xingjun Ma, Qiuhong Ke, Yisen Wang, James Bailey
Workshop
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack
Sungmin Cha, Naeun Ko, YoungJoon Yoo, Taesup Moon
Workshop
Out of Distribution Detection and Adversarial Attacks on Deep Neural Networks for Robust Medical Image Analysis
Anisie Uwimana, Ransalu Senanayake
Workshop
Attacking Graph Classification via Bayesian Optimisation
Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong
Workshop
Adversarial Semantic Contour for Object Detection
Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu
Workshop
Meta Adversarial Training against Universal Patches
Jan Hendrik Metzen, Nicole Finnie, Robin Hutmacher
Workshop
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity
Praneeth Vepakomma, Ramesh Raskar
Workshop
Counterfactual Explanations for Graph Neural Networks
Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke, Fabrizio Silvestri
Workshop
Rethinking compactness in deep neural networks
Kateryna Chumachenko, Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Workshop
Improved Regret Bounds for Online Submodular Maximization
Omid Sadeghi, Maryam Fazel
Workshop
Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Workshop
Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
Learning to Delegate for Large-scale Vehicle Routing
Sirui Li, Zhongxia Yan, Cathy Wu
Workshop
Interactive Teaching for Imbalanced Data Summarization
Farhad Pourkamali-Anaraki, Walter Bennette
Workshop
Failures of Uncertainty Estimation on Out-Of-Distribution Samples: Experimental Results from Medical Applications Lead to Theoretical Insights
Workshop
MetaDataset: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts
Weixin Liang, James Zou, Weixin Liang
Workshop
Measuring Fairness in Generative Models
Chris Teo, Ngai-Man Cheung
Workshop
Information-Guided Sampling for Low-Rank Matrix Completion
Simon Mak, Shaowu Yuchi, Yao Xie
Workshop
Sliced Mutual Information: A Scalable Measure of Statistical Dependence
Ziv Goldfeld, Kristjan Greenewald
Workshop
Prediction-focused Mixture Models
Abhishek Sharma, Sanjana Narayanan, Catherine Zeng, Finale Doshi-Velez
Workshop
Data-Dependent PAC-Bayesian Bounds in the Random-Subset Setting with Applications to Neural Networks
Fredrik Hellström, Giuseppe Durisi
Workshop
Out-of-Distribution Robustness in Deep Learning Compression
Eric Lei, Hamed Hassani
Workshop
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Shengyuan Hu, Steven Wu, Virginia Smith
Workshop
Lossless Compression of Efficient Private Local Randomizers
Vitaly Feldman, Kunal Talwar
Workshop
Randomized Response with Prior and Applications to Learning with Label Differential Privacy
Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
Workshop
Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation
Kunal Talwar
Workshop
Concurrent Composition of Differential Privacy
Salil Vadhan, Tianhao Wang
Workshop
Optimal Accounting of Differential Privacy via Characteristic Function
Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang
Workshop
Outlier-Robust Optimal Transport with Applications to Generative Modeling and Data Privacy
Sloan Nietert, Rachel Cummings, Ziv Goldfeld
Workshop
On the Renyi Differential Privacy of the Shuffle Model
Antonious M Girgis, Deepesh Data, Suhas Diggavi, Ananda Theertha Suresh, Peter Kairouz
Workshop
Privacy Amplification by Bernoulli Sampling
Jacob Imola, Kamalika Chaudhuri
Workshop
Prior-Aware Distribution Estimation for Differential Privacy
Yuchao Tao, Johes Bater, Ashwin Machanavajjhala
Workshop
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty
Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis
Workshop
Privacy Amplification by Subsampling in Time Domain
Tatsuki Koga, Casey M Meehan, Kamalika Chaudhuri
Workshop
Neural Fixed-Point Acceleration for Convex Optimization
Shobha Venkataraman, Brandon Amos