407 Results

Expo Talk Panel
Sun 2:45 End-to-end Bayesian inference workflows in TensorFlow Probability
Mary Ellen Perry
Expo Talk Panel
Sun 6:30 Baidu AutoDL: Automated and Interpretable Deep Learning
Bolei Zhou, Yi Yang, Quanshi Zhang, Dejing Dou, Haoyi Xiong, Jiahui Yu, Humphrey Shi, Linchao Zhu, Xingjian Li
Expo Talk Panel
Sun 7:45 AutoAI at IBM Research
Mary Ellen Perry
Expo Demonstration
Sun 9:00 RXNMapper – AI Explainability 360 - Command Line AI – COVID-19 Molecule Explorer
Mary Ellen Perry
AffinityWorkshop
Mon 5:00 LatinX in AI Workshop
Nils Murrugarra-Llerena, Pedro Braga, Walter Mayor, Karla Caballero, Ivan Dario Arraut Guerrero, Juan Banda, Fabian Latorre, Kevin Bello, Leobardo Morales, Leonel Rozo, Angy M Flores-Saravia
Tutorial
Mon 5:00 Parameter-free Online Optimization
Francesco Orabona, Ashok Cutkosky
Tutorial
Mon 5:00 Recent Advances in High-Dimensional Robust Statistics
Ilias Diakonikolas
AffinityWorkshop
Mon 7:50 When do ranking algorithms reinforce, replicate, or weaken inequalities in directed social networks?
Lisette Espín
Tutorial
Mon 8:00 Submodular Optimization: From Discrete to Continuous and Back
Hamed Hassani, Amin Karbasi
AffinityWorkshop
Mon 9:45 Breakout Session 3.4: Mining Biological and Biomedical Data with Graph-Based Algorithms
AffinityWorkshop
Mon 14:00 Queer in AI
Ti John, William Agnew, Alex Markham, Manu Saraswat, Raphael Gontijo Lopes
Poster
Tue 7:00 On the Noisy Gradient Descent that Generalizes as SGD
Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu
Poster
Tue 7:00 Evaluating the Performance of Reinforcement Learning Algorithms
Scott Jordan, Yash Chandak, Daniel Cohen, Mengxue Zhang, Philip Thomas
Poster
Tue 7:00 Efficient nonparametric statistical inference on population feature importance using Shapley values
Brian Williamson, Jean Feng
Poster
Tue 7:00 Confidence-Aware Learning for Deep Neural Networks
Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang
Poster
Tue 7:00 Generating Programmatic Referring Expressions via Program Synthesis
Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik
Poster
Tue 7:00 Layered Sampling for Robust Optimization Problems
Hu Ding, Zixiu Wang
Poster
Tue 7:00 Streaming Submodular Maximization under a k-Set System Constraint
Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi
Poster
Tue 7:00 Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions
Kaito Fujii
Poster
Tue 7:00 Stochastic Optimization for Non-convex Inf-Projection Problems
Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang
Poster
Tue 7:00 Interpolation between Residual and Non-Residual Networks
Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi
Poster
Tue 7:00 Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
Yaodong Yang, Jianye Hao, Guangyong Chen, Hongyao Tang, Yingfeng Chen, Yujing Hu, Changjie Fan, Zhongyu Wei
Poster
Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO, Hansi Yang, Bo Han, Gang Niu, James Kwok
Poster
Tue 7:00 Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data
Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yufeng Li, Zhi-Hua Zhou
Poster
Tue 7:00 Optimizing for the Future in Non-Stationary MDPs
Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip Thomas
Poster
Tue 7:00 Deep Divergence Learning
Kubra Cilingir, Rachel Manzelli, Brian Kulis
Poster
Tue 7:00 Streaming k-Submodular Maximization under Noise subject to Size Constraint
Lan N. Nguyen, My T. Thai
Poster
Tue 7:00 Self-Concordant Analysis of Frank-Wolfe Algorithms
Pavel Dvurechenskii, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl
Poster
Tue 7:00 On the Generalization Effects of Linear Transformations in Data Augmentation
Sen Wu, Hongyang Zhang, Gregory Valiant, Christopher Re
Poster
Tue 7:00 Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner
Poster
Tue 7:00 MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
XICHUAN ZHOU, YiCong Peng, Chunqiao Long, Fengbo Ren, Cong Shi
Poster
Tue 7:00 Zeno++: Robust Fully Asynchronous SGD
Cong Xie, Sanmi Koyejo, Indranil Gupta
Poster
Tue 7:00 AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang
Poster
Tue 7:00 Familywise Error Rate Control by Interactive Unmasking
Boyan Duan, Aaditya Ramdas, Larry Wasserman
Poster
Tue 7:00 Customizing ML Predictions for Online Algorithms
Keerti Anand, Rong Ge, Debmalya Panigrahi
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong, Bo Zeng
Poster
Tue 7:00 Two Routes to Scalable Credit Assignment without Weight Symmetry
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena, Surya Ganguli, Jon Bloom, Daniel Yamins
Poster
Tue 7:00 Asynchronous Coagent Networks
James Kostas, Chris Nota, Philip Thomas
Poster
Tue 7:00 Causal Strategic Linear Regression
Yonadav Shavit, Ben Edelman, Brian Axelrod
Poster
Tue 7:00 Combinatorial Pure Exploration for Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
Poster
Tue 7:00 Loss Function Search for Face Recognition
Xiaobo Wang, Shuo Wang, Cheng Chi, Shifeng Zhang, Tao Mei
Poster
Tue 7:00 Distance Metric Learning with Joint Representation Diversification
Xu Chu, Yang Lin, Yasha Wang, Xiting Wang, Hailong Yu, Xin Gao, Qi Tong
Poster
Tue 7:00 Accelerated Stochastic Gradient-free and Projection-free Methods
Feihu Huang, Lue Tao, Songcan Chen
Poster
Tue 7:00 A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton
Poster
Tue 7:00 Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints
Akbar Rafiey, Yuichi Yoshida
Poster
Tue 7:00 FedBoost: A Communication-Efficient Algorithm for Federated Learning
Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh
Poster
Tue 7:00 Taylor Expansion Policy Optimization
Yunhao Tang, Michal Valko, Remi Munos
Poster
Tue 7:00 Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
Runchao Ma, Qihang Lin, Tianbao Yang
Poster
Tue 8:00 An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk
Poster
Tue 8:00 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
Poster
Tue 8:00 Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization
Rie Johnson, Tong Zhang
Poster
Tue 8:00 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
Shangtong Zhang, Bo Liu, Shimon Whiteson
Poster
Tue 8:00 Informative Dropout for Robust Representation Learning: A Shape-bias Perspective
Baifeng Shi, Dinghuai Zhang, Qi Dai, Zhanxing Zhu, Yadong Mu, Jingdong Wang
Poster
Tue 8:00 The Tree Ensemble Layer: Differentiability meets Conditional Computation
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
Poster
Tue 8:00 RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr
Xingjian Li, Haoyi Xiong, Haozhe An, Cheng-Zhong Xu, Dejing Dou
Poster
Tue 8:00 Differentially Private Set Union
Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin
Poster
Tue 8:00 Invariant Risk Minimization Games
Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu
Poster
Tue 8:00 Batch Reinforcement Learning with Hyperparameter Gradients
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
Poster
Tue 8:00 Discount Factor as a Regularizer in Reinforcement Learning
Ron Amit, Ron Meir, Kamil Ciosek
Poster
Tue 8:00 AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real, Chen Liang, David So, Quoc Le
Poster
Tue 8:00 Stronger and Faster Wasserstein Adversarial Attacks
Kaiwen Wu, Allen Wang, Yaoliang Yu
Poster
Tue 9:00 Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu, Vladimir Braverman, Lin Yang
Poster
Tue 9:00 Streaming Coresets for Symmetric Tensor Factorization
Supratim Shit, Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta
Poster
Tue 9:00 Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam
Poster
Tue 9:00 Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Poster
Tue 9:00 Fast OSCAR and OWL Regression via Safe Screening Rules
Runxue Bao, Bin Gu, Heng Huang
Poster
Tue 9:00 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali Teshnizi, Saber Salehkaleybar, Negar Kiyavash
Poster
Tue 9:00 Nearly Linear Row Sampling Algorithm for Quantile Regression
Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
Poster
Tue 9:00 Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil
Poster
Tue 9:00 Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Rui Wang, Joel Lehman, Aditya Rawal, Jiale Zhi, Yulun Li, Jeffrey Clune, Ken Stanley
Poster
Tue 9:00 Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
Dylan Foster, Alexander Rakhlin
Poster
Tue 9:00 Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter
Poster
Tue 9:00 Variance Reduction in Stochastic Particle-Optimization Sampling
Jianyi Zhang, Yang Zhao, Changyou Chen
Poster
Tue 9:00 Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach
Junzhe Zhang
Poster
Tue 9:00 Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
Poster
Tue 9:00 Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
Poster
Tue 10:00 Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Adam Stooke, Joshua Achiam, Pieter Abbeel
Poster
Tue 10:00 Learning To Stop While Learning To Predict
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Poster
Tue 10:00 Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman, Ken Stanley, Jeffrey Clune
Poster
Tue 10:00 Error Estimation for Sketched SVD via the Bootstrap
Miles Lopes, N. Benjamin Erichson, Michael Mahoney
Poster
Tue 10:00 Sub-Goal Trees -- a Framework for Goal-Based Reinforcement Learning
Tom Jurgenson, Or Avner, Edward Groshev, Aviv Tamar
Poster
Tue 10:00 Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers
Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph Gonzalez
Poster
Tue 10:00 Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov
Poster
Tue 10:00 Online Control of the False Coverage Rate and False Sign Rate
Asaf Weinstein, Aaditya Ramdas
Poster
Tue 10:00 SoftSort: A Continuous Relaxation for the argsort Operator
Sebastian Prillo, Julian M Eisenschlos
Poster
Tue 10:00 A simpler approach to accelerated optimization: iterative averaging meets optimism
Pooria Joulani, Anant Raj, András György, Csaba Szepesvari
Poster
Tue 10:00 Optimally Solving Two-Agent Decentralized POMDPs Under One-Sided Information Sharing
Yuxuan Xie, Jilles Dibangoye, Olivier Buffet
Poster
Tue 10:00 Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
Poster
Tue 10:00 Explainable k-Means and k-Medians Clustering
Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost
Poster
Tue 10:00 Structured Prediction with Partial Labelling through the Infimum Loss
Vivien Cabannnes, Alessandro Rudi, Francis Bach
Poster
Tue 11:00 Near-linear time Gaussian process optimization with adaptive batching and resparsification
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
Poster
Tue 11:00 Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain
Poster
Tue 11:00 Smaller, more accurate regression forests using tree alternating optimization
Arman Zharmagambetov, Miguel Carreira-Perpinan
Poster
Tue 11:00 Bandits with Adversarial Scaling
Thodoris Lykouris, Vahab Mirrokni, Renato Leme
Poster
Tue 11:00 Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, D.J. Sutherland
Poster
Tue 11:00 Online metric algorithms with untrusted predictions
Antonios Antoniadis, Christian Coester, Marek Elias, Adam Polak, Bertrand Simon
Poster
Tue 11:00 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
Poster
Tue 11:00 Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
Basil Saeed, Snigdha Panigrahi, Caroline Uhler
Poster
Tue 11:00 Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer
Alexey Drutsa
Poster
Tue 12:00 TaskNorm: Rethinking Batch Normalization for Meta-Learning
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E Turner
Poster
Tue 12:00 Weakly-Supervised Disentanglement Without Compromises
Francesco Locatello, Ben Poole, Gunnar Ratsch, Bernhard Schölkopf, Olivier Bachem, Michael Tschannen
Poster
Tue 12:00 Multi-step Greedy Reinforcement Learning Algorithms
Manan Tomar, Yonathan Efroni, Mohammad Ghavamzadeh
Poster
Tue 12:00 Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization
GEOFFREY Negiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
Poster
Tue 12:00 Word-Level Speech Recognition With a Letter to Word Encoder
Ronan Collobert, Awni Hannun, Gabriel Synnaeve
Poster
Tue 13:00 Meta-learning with Stochastic Linear Bandits
Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
Poster
Tue 13:00 Uncertainty Estimation Using a Single Deep Deterministic Neural Network
Joost van Amersfoort, Lewis Smith, Yee-Whye Teh, Yarin Gal
Poster
Tue 13:00 Supervised learning: no loss no cry
Richard Nock, Aditya Menon
Poster
Tue 13:00 Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization
Hien Le, Nicolas Gillis, Panagiotis Patrinos
Poster
Tue 13:00 Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks
David Stutz, Matthias Hein, Bernt Schiele
Poster
Tue 13:00 Optimal Randomized First-Order Methods for Least-Squares Problems
Jonathan Lacotte, Mert Pilanci
Poster
Tue 13:00 Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
Umut Simsekli, Lingjiong Zhu, Yee-Whye Teh, Mert Gurbuzbalaban
Poster
Tue 13:00 Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun
Poster
Tue 13:00 Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses
Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alche-Buc
Poster
Tue 14:00 Optimal Estimator for Unlabeled Linear Regression
Hang Zhang, Ping Li
Poster
Tue 14:00 Logarithmic Regret for Learning Linear Quadratic Regulators Efficiently
Asaf Cassel, Alon Cohen, Tomer Koren
Poster
Tue 14:00 Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure
John Sipple
Poster
Tue 14:00 Finding trainable sparse networks through Neural Tangent Transfer
Tianlin Liu, Friedemann Zenke
Poster
Tue 15:00 Unsupervised Speech Decomposition via Triple Information Bottleneck
Kaizhi Qian, Yang Zhang, Shiyu Chang, Mark Hasegawa-Johnson, David Cox
Poster
Tue 15:00 When deep denoising meets iterative phase retrieval
Yaotian Wang, Xiaohang Sun, Jason Fleischer
Poster
Tue 15:00 Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka
Poster
Tue 15:00 Thompson Sampling Algorithms for Mean-Variance Bandits
Qiuyu Zhu, Vincent Tan
Poster
Tue 15:00 Interferometric Graph Transform: a Deep Unsupervised Graph Representation
Edouard Oyallon
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Tue 18:00 Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Kei Ota, Tomoaki Oiki, Devesh Jha, Toshisada Mariyama, Daniel Nikovski
Poster
Tue 18:00 Learning De-biased Representations with Biased Representations
Hyojin Bahng, SANGHYUK CHUN, Sangdoo Yun, Jaegul Choo, Seong Joon Oh
Poster
Tue 18:00 Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
Pan Zhou, Xiao-Tong Yuan
Poster
Tue 18:00 Striving for Simplicity and Performance in Off-Policy DRL: Output Normalization and Non-Uniform Sampling
Che Wang, Yanqiu Wu, Quan Vuong, Keith Ross
Poster
Tue 18:00 Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems
Kaixuan Wei, Angelica I Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, Hua Huang
Poster
Tue 18:00 Learning with Feature and Distribution Evolvable Streams
Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou
Poster
Tue 18:00 Attacks Which Do Not Kill Training Make Adversarial Learning Stronger
Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan Kankanhalli
Poster
Tue 19:00 DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths
Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan ZENG, Yuan Yao
Poster
Tue 19:00 Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Poster
Wed 5:00 An Accelerated DFO Algorithm for Finite-sum Convex Functions
Yuwen Chen, Antonio Orvieto, Aurelien Lucchi
Poster
Wed 5:00 Robust and Stable Black Box Explanations
Hima Lakkaraju, Nino Arsov, Osbert Bastani
Poster
Wed 5:00 Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff
Poster
Wed 5:00 Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
Poster
Wed 5:00 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
Bo Han, Gang Niu, Xingrui Yu, QUANMING YAO, Miao Xu, Ivor Tsang, Masashi Sugiyama
Poster
Wed 5:00 Fair k-Centers via Maximum Matching
Matthew Jones, Huy Nguyen, Thy Nguyen
Poster
Wed 5:00 Consistent Estimators for Learning to Defer to an Expert
Hussein Mozannar, David Sontag
Poster
Wed 5:00 Second-Order Provable Defenses against Adversarial Attacks
Sahil Singla, Soheil Feizi
Poster
Wed 5:00 Adversarial Risk via Optimal Transport and Optimal Couplings
Muni Sreenivas Pydi, Varun Jog
Poster
Wed 5:00 What can I do here? A Theory of Affordances in Reinforcement Learning
Khimya Khetarpal, Zafarali Ahmed, Gheorghe Comanici, Dave Abel, Doina Precup
Poster
Wed 5:00 Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?
Hongchang Gao, Heng Huang
Poster
Wed 5:00 An Optimistic Perspective on Offline Deep Reinforcement Learning
Rishabh Agarwal, Dale Schuurmans, Mohammad Norouzi
Poster
Wed 5:00 Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Steven Wu
Poster
Wed 5:00 Moniqua: Modulo Quantized Communication in Decentralized SGD
Yucheng Lu, Christopher De Sa
Poster
Wed 5:00 Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games
Darren Lin, Zhengyuan Zhou, Panayotis Mertikopoulos, Michael Jordan
Poster
Wed 5:00 Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics
Debjani Saha, Candice Schumann, Duncan McElfresh, John P Dickerson, Michelle Mazurek, Michael Tschantz
Poster
Wed 5:00 Learning What to Defer for Maximum Independent Sets
Sungsoo Ahn, Younggyo Seo, Jinwoo Shin
Poster
Wed 5:00 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
Jie Xu, Yunsheng Tian, Pingchuan Ma, Daniela Rus, Shinjiro Sueda, Wojciech Matusik
Poster
Wed 5:00 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba
Poster
Wed 5:00 Optimal approximation for unconstrained non-submodular minimization
Marwa El Halabi, Stefanie Jegelka
Poster
Wed 8:00 Negative Sampling in Semi-Supervised learning
John Chen, Vatsal Shah, Tasos Kyrillidis
Poster
Wed 8:00 A Sequential Self Teaching Approach for Improving Generalization in Sound Event Recognition
Anurag Kumar, Vamsi Krishna Ithapu
Poster
Wed 8:00 Online mirror descent and dual averaging: keeping pace in the dynamic case
Huang Fang, Nick Harvey, Victor Sanches Portella, Michael Friedlander
Poster
Wed 8:00 Boosting Deep Neural Network Efficiency with Dual-Module Inference
Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
Poster
Wed 8:00 Adversarial Filters of Dataset Biases
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew Peters, Ashish Sabharwal, Yejin Choi
Poster
Wed 8:00 Decoupled Greedy Learning of CNNs
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Poster
Wed 8:00 Choice Set Optimization Under Discrete Choice Models of Group Decisions
Kiran Tomlinson, Austin Benson
Poster
Wed 8:00 Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
Poster
Wed 8:00 Superpolynomial Lower Bounds for Learning One-Layer Neural Networks using Gradient Descent
Surbhi Goel, Aravind Gollakota, Zhihan Jin, Sushrut Karmalkar, Adam Klivans
Poster
Wed 8:00 Structure Adaptive Algorithms for Stochastic Bandits
Rémy Degenne, Han Shao, Wouter Koolen
Poster
Wed 8:00 Exploration Through Reward Biasing: Reward-Biased Maximum Likelihood Estimation for Stochastic Multi-Armed Bandits
Xi Liu, Ping-Chun Hsieh, Yu Heng Hung, Anirban Bhattacharya, P. Kumar
Poster
Wed 8:00 Coresets for Clustering in Graphs of Bounded Treewidth
Daniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu
Poster
Wed 8:00 The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phil Gibbons
Poster
Wed 8:00 Safe screening rules for L0-regression from Perspective Relaxations
Alper Atamturk, Andres Gomez
Poster
Wed 8:00 (Locally) Differentially Private Combinatorial Semi-Bandits
Xiaoyu Chen, Kai Zheng, Zixin(Jack) Zhou, Yunchang Yang, Wei Chen, Liwei Wang
Poster
Wed 8:00 Identifying the Reward Function by Anchor Actions
Sinong Geng, Houssam Nassif, Charlie Manzanares, Max Reppen, Ronnie Sircar
Poster
Wed 8:00 Circuit-Based Intrinsic Methods to Detect Overfitting
Satrajit Chatterjee, Alan Mishchenko
Poster
Wed 8:00 Structured Linear Contextual Bandits: A Sharp and Geometric Smoothed Analysis
Vidyashankar Sivakumar, Steven Wu, Arindam Banerjee
Poster
Wed 8:00 Robust Outlier Arm Identification
Yinglun Zhu, Sumeet Katariya, Robert Nowak
Poster
Wed 8:00 Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory
Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu
Poster
Wed 8:00 Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael Jordan
Poster
Wed 8:00 Communication-Efficient Distributed PCA by Riemannian Optimization
Long-Kai Huang, Sinno Jialin Pan
Poster
Wed 9:00 Provable Self-Play Algorithms for Competitive Reinforcement Learning
Yu Bai, Chi Jin
Poster
Wed 9:00 Low-Variance and Zero-Variance Baselines for Extensive-Form Games
Trevor Davis, Martin Schmid, Michael Bowling
Poster
Wed 9:00 Accountable Off-Policy Evaluation With Kernel Bellman Statistics
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Poster
Wed 9:00 Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten Borgwardt
Poster
Wed 9:00 Cooperative Multi-Agent Bandits with Heavy Tails
Abhimanyu Dubey, Alex `Sandy' Pentland
Poster
Wed 9:00 Dual Mirror Descent for Online Allocation Problems
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Poster
Wed 9:00 Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations
Robert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg
Poster
Wed 9:00 Hallucinative Topological Memory for Zero-Shot Visual Planning
Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
Poster
Wed 9:00 Flexible and Efficient Long-Range Planning Through Curious Exploration
Aidan Curtis, Minjian Xin, Dilip Arumugam, Kevin Feigelis, Daniel Yamins
Poster
Wed 10:00 Data Valuation using Reinforcement Learning
Jinsung Yoon, Sercan Arik, Tomas Pfister
Poster
Wed 10:00 Handling the Positive-Definite Constraint in the Bayesian Learning Rule
Wu Lin, Mark Schmidt, Emti Khan
Poster
Wed 10:00 Self-supervised Label Augmentation via Input Transformations
Hankook Lee, Sung Ju Hwang, Jinwoo Shin
Poster
Wed 10:00 Learning Representations that Support Extrapolation
Taylor Webb, Zachary Dulberg, Steven Frankland, Alexander Petrov, Randall O'Reilly, Jonathan Cohen
Poster
Wed 10:00 How to Solve Fair k-Center in Massive Data Models
Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy
Poster
Wed 10:00 Fast computation of Nash Equilibria in Imperfect Information Games
Remi Munos, Julien Perolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls
Poster
Wed 10:00 Continuous-time Lower Bounds for Gradient-based Algorithms
Michael Muehlebach, Michael Jordan
Poster
Wed 10:00 A Game Theoretic Framework for Model Based Reinforcement Learning
Aravind Rajeswaran, Igor Mordatch, Vikash Kumar
Poster
Wed 10:00 The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
Wenbo Ren, Jia Liu, Ness Shroff
Poster
Wed 10:00 Stochastic bandits with arm-dependent delays
Anne Gael Manegueu, Claire Vernade, Alexandra Carpentier, Michal Valko
Poster
Wed 10:00 Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, Moritz Hardt
Poster
Wed 10:00 Evolutionary Topology Search for Tensor Network Decomposition
Chao Li, Zhun Sun
Poster
Wed 11:00 From Local SGD to Local Fixed-Point Methods for Federated Learning
Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent CONDAT, Peter Richtarik
Poster
Wed 11:00 Revisiting Fundamentals of Experience Replay
William Fedus, Prajit Ramachandran, Rishabh Agarwal, Yoshua Bengio, Hugo Larochelle, Mark Rowland, Will Dabney
Poster
Wed 11:00 Gamification of Pure Exploration for Linear Bandits
Rémy Degenne, Pierre Menard, Xuedong Shang, Michal Valko
Poster
Wed 11:00 DeBayes: a Bayesian Method for Debiasing Network Embeddings
Maarten Buyl, Tijl De Bie
Poster
Wed 11:00 A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
Pan Xu, Quanquan Gu
Poster
Wed 12:00 Optimal Continual Learning has Perfect Memory and is NP-hard
Jeremias Knoblauch, Hisham Husain, Tom Diethe
Poster
Wed 12:00 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
Marc Abeille, Alessandro Lazaric
Poster
Wed 12:00 A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 12:00 Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time
Zahra Monfared, Daniel Durstewitz
Poster
Wed 12:00 Automatic Reparameterisation of Probabilistic Programs
Maria Gorinova, Dave Moore, Matt Hoffman
Poster
Wed 12:00 Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Rasmus Pagh
Poster
Wed 12:00 Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition
Alex Gittens, Kareem Aggour, Bülent Yener
Poster
Wed 12:00 Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtarik
Poster
Wed 12:00 Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
Alexey Drutsa
Poster
Wed 13:00 State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
William Wilkinson, Paul Chang, Michael Andersen, Arno Solin
Poster
Wed 13:00 Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, François Fleuret
Poster
Wed 13:00 Fast Adaptation to New Environments via Policy-Dynamics Value Functions
Roberta Raileanu, Max Goldstein, Arthur Szlam, Facebook Rob Fergus
Poster
Wed 13:00 Involutive MCMC: a Unifying Framework
Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry Vetrov
Poster
Wed 13:00 Up or Down? Adaptive Rounding for Post-Training Quantization
Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort
Poster
Wed 13:00 Growing Adaptive Multi-hyperplane Machines
Nemanja Djuric, Zhuang Wang, Slobodan Vucetic
Poster
Wed 13:00 Continuous Time Bayesian Networks with Clocks
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
Poster
Wed 13:00 Quantum Boosting
Srinivasan Arunachalam, Reevu Maity
Poster
Wed 14:00 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia, Haipeng Luo, Hiteshi Sharma, Rahul Jain
Poster
Wed 14:00 Lifted Disjoint Paths with Application in Multiple Object Tracking
Andrea Hornakova, Roberto Henschel, Bodo Rosenhahn, Paul Swoboda
Poster
Wed 14:00 Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning
Alberto Maria Metelli, Flavio Mazzolini, Lorenzo Bisi, Luca Sabbioni, Marcello Restelli
Poster
Wed 14:00 VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing
Zoltán Á. Milacski, Barnabás Póczos, Andras Lorincz
Poster
Wed 14:00 Explicit Gradient Learning for Black-Box Optimization
Elad Sarafian, Mor Sinay, yoram louzoun, Noa Agmon, Sarit Kraus
Poster
Wed 14:00 Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs
Aditya Rajagopal, Diederik Vink, Stylianos Venieris, Christos-Savvas Bouganis
Poster
Wed 15:00 LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction
Vlad Niculae, Andre Filipe Torres Martins
Poster
Wed 15:00 Agent57: Outperforming the Atari Human Benchmark
Adrià Puigdomenech Badia, Bilal Piot, Steven Kapturowski, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Guo, Charles Blundell
Poster
Wed 15:00 Haar Graph Pooling
Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan
Poster
Wed 16:00 Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Poster
Wed 16:00 On Lp-norm Robustness of Ensemble Decision Stumps and Trees
Yihan Wang, Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh
Poster
Wed 16:00 Boosted Histogram Transform for Regression
Yuchao Cai, Hanyuan Hang, Hanfang Yang, Zhouchen Lin
Poster
Wed 16:00 From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics
Sai Ganesh Nagarajan, David Balduzzi, Georgios Piliouras
Poster
Wed 16:00 Online Dense Subgraph Discovery via Blurred-Graph Feedback
Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama
Poster
Thu 6:00 Sparsified Linear Programming for Zero-Sum Equilibrium Finding
Brian Zhang, Tuomas Sandholm
Poster
Thu 6:00 Learning Selection Strategies in Buchberger’s Algorithm
Dylan Peifer, Michael Stillman, Daniel Halpern-Leistner
Poster
Thu 6:00 Privately detecting changes in unknown distributions
Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang
Poster
Thu 6:00 Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion
Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie Su
Poster
Thu 6:00 Differentiable Product Quantization for End-to-End Embedding Compression
Ting Chen, Lala Li, Yizhou Sun
Poster
Thu 6:00 T-GD: Transferable GAN-generated Images Detection Framework
Hyeonseong Jeon, Young Oh Bang, Junyaup Kim, Simon Woo
Poster
Thu 6:00 Upper bounds for Model-Free Row-Sparse Principal Component Analysis
Guanyi Wang, Santanu Dey
Poster
Thu 6:00 Convex Calibrated Surrogates for the Multi-Label F-Measure
Mingyuan Zhang, Harish Ramaswamy, Shivani Agarwal
Poster
Thu 6:00 Constrained Markov Decision Processes via Backward Value Functions
Harsh Satija, Philip Amortila, Joelle Pineau
Poster
Thu 6:00 Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski, David Cheikhi, Jared Quincy Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani
Poster
Thu 6:00 Deep Reinforcement Learning with Smooth Policy
Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
Poster
Thu 6:00 Towards Accurate Post-training Network Quantization via Bit-Split and Stitching
Peisong Wang, Qiang Chen, Xiangyu He, Jian Cheng
Poster
Thu 6:00 Error-Bounded Correction of Noisy Labels
Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen
Poster
Thu 6:00 On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
Darren Lin, Chi Jin, Michael Jordan
Poster
Thu 6:00 Input-Sparsity Low Rank Approximation in Schatten Norm
Yi Li, David Woodruff
Poster
Thu 6:00 Acceleration through spectral density estimation
Fabian Pedregosa, Damien Scieur
Poster
Thu 6:00 Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon, Sanjiv Kumar
Poster
Thu 6:00 Fiedler Regularization: Learning Neural Networks with Graph Sparsity
Edric Tam, David Dunson
Poster
Thu 6:00 Meta Variance Transfer: Learning to Augment from the Others
Seong-Jin Park, Seungju Han, Ji-won Baek, Insoo Kim, Juhwan Song, Hae Beom Lee, Jae-Joon Han, Sung Ju Hwang
Poster
Thu 6:00 Rigging the Lottery: Making All Tickets Winners
Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
Poster
Thu 6:00 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Quoc Tran-Dinh, Nate H Pham, Lam Nguyen
Poster
Thu 6:00 Countering Language Drift with Seeded Iterated Learning
Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, Olivier Pietquin
Poster
Thu 6:00 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin LIANG
Poster
Thu 6:00 Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
Kyriakos Axiotis, Maxim Sviridenko
Poster
Thu 6:00 New Oracle-Efficient Algorithms for Private Synthetic Data Release
Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Steven Wu
Poster
Thu 6:00 Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima
Poster
Thu 6:00 Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
Poster
Thu 6:00 Black-Box Methods for Restoring Monotonicity
Evangelia Gergatsouli, Brendan Lucier, Christos Tzamos
Poster
Thu 6:00 Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics
Matt Hoffman, Yian Ma
Poster
Thu 6:00 On the Expressivity of Neural Networks for Deep Reinforcement Learning
Kefan Dong, Yuping Luo, Tianhe (Kevin) Yu, Chelsea Finn, Tengyu Ma
Poster
Thu 6:00 Almost Tune-Free Variance Reduction
Bingcong Li, Lingda Wang, Georgios B. Giannakis
Poster
Thu 6:00 A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Brian Brubach, Darshan Chakrabarti, John P Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
Poster
Thu 6:00 Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag
Poster
Thu 6:00 Born-again Tree Ensembles
Thibaut Vidal, Maximilian Schiffer
Poster
Thu 6:00 Refined bounds for algorithm configuration: The knife-edge of dual class approximability
Nina Balcan, Tuomas Sandholm, Ellen Vitercik
Poster
Thu 6:00 Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards
Aadirupa Saha, Pierre Gaillard, Michal Valko
Poster
Thu 6:00 Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan
Poster
Thu 7:00 Goal-Aware Prediction: Learning to Model What Matters
Suraj Nair, Silvio Savarese, Chelsea Finn
Poster
Thu 7:00 No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David Pennock, Chara Podimata, Jenn Wortman Vaughan
Poster
Thu 7:00 Improving generalization by controlling label-noise information in neural network weights
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
Poster
Thu 7:00 Online Learning with Imperfect Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit
Poster
Thu 7:00 Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc Le, Qiang Liu, Dale Schuurmans
Poster
Thu 7:00 On hyperparameter tuning in general clustering problemsm
Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
Poster
Thu 7:00 Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False
Zehua Lai, Lek-Heng Lim
Poster
Thu 7:00 Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games
Youzhi Zhang, Bo An
Poster
Thu 7:00 On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu
Poster
Thu 7:00 Graph Optimal Transport for Cross-Domain Alignment
Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu
Poster
Thu 7:00 The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation
Zhe Feng, David Parkes, Haifeng Xu
Poster
Thu 7:00 Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei
Poster
Thu 7:00 Efficient Continuous Pareto Exploration in Multi-Task Learning
Pingchuan Ma, Tao Du, Wojciech Matusik
Poster
Thu 7:00 Optimal Differential Privacy Composition for Exponential Mechanisms
Jinshuo Dong, David Durfee, Ryan Rogers
Poster
Thu 7:00 Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
Michael Zhu, Chang Liu, Jun Zhu
Poster
Thu 7:00 Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Tom Fei, Qiantong Xu, Chengrun Yang
Poster
Thu 7:00 Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
Ying Jin, Zhaoran Wang, Junwei Lu
Poster
Thu 7:00 Variational Inference for Sequential Data with Future Likelihood Estimates
Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
Poster
Thu 8:00 Optimizing Data Usage via Differentiable Rewards
Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Jaime Carbonell, Graham Neubig
Poster
Thu 8:00 Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels
Lu Jiang, Di Huang, Mason Liu, Weilong Yang
Poster
Thu 8:00 Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Poster
Thu 8:00 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang
Poster
Thu 8:00 High-dimensional Robust Mean Estimation via Gradient Descent
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
Poster
Thu 8:00 The Performance Analysis of Generalized Margin Maximizers on Separable Data
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Poster
Thu 8:00 Momentum-Based Policy Gradient Methods
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Poster
Thu 8:00 Generalized and Scalable Optimal Sparse Decision Trees
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer
Poster
Thu 8:00 Sparse Sinkhorn Attention
Yi Tay, Dara Bahri, Liu Yang, Don Metzler, Da-Cheng Juan
Poster
Thu 8:00 Learning Mixtures of Graphs from Epidemic Cascades
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Poster
Thu 8:00 Progressive Identification of True Labels for Partial-Label Learning
Jiaqi Lv, Miao Xu, LEI FENG, Gang Niu, Xin Geng, Masashi Sugiyama
Poster
Thu 9:00 Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning
Sai Krishna Gottipati, Boris Sattarov, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Shengchao Liu, Simon Blackburn, Karam Thomas, Connor Coley, Jian Tang, Sarath Chandar, Yoshua Bengio
Poster
Thu 9:00 Improved Optimistic Algorithms for Logistic Bandits
Louis Faury, Marc Abeille, Clément Calauzènes, Olivier Fercoq
Poster
Thu 9:00 Bio-Inspired Hashing for Unsupervised Similarity Search
Chaitanya Ryali, John Hopfield, Leopold Grinberg, Dmitry Krotov
Poster
Thu 9:00 CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Michael Laskin, Aravind Srinivas, Pieter Abbeel
Poster
Thu 9:00 From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
Aadirupa Saha, Aditya Gopalan
Poster
Thu 9:00 A Distributional Framework For Data Valuation
Amirata Ghorbani, Michael Kim, James Zou
Poster
Thu 9:00 Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu
Poster
Thu 9:00 Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions
Michael Chang, Sid Kaushik, S. Matthew Weinberg, Thomas Griffiths, Sergey Levine
Poster
Thu 9:00 Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking
Haoran Sun, Songtao Lu, Mingyi Hong
Poster
Thu 9:00 Accelerated Message Passing for Entropy-Regularized MAP Inference
Jonathan Lee, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Invited Talk
Thu 10:00 Quantum Machine Learning : Prospects and Challenges
Iordanis Kerenidis
Poster
Thu 12:00 Graph-based Nearest Neighbor Search: From Practice to Theory
Liudmila Prokhorenkova, Aleksandr Shekhovtsov
Poster
Thu 12:00 Missing Data Imputation using Optimal Transport
Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
Poster
Thu 12:00 Composable Sketches for Functions of Frequencies: Beyond the Worst Case
Edith Cohen, Ofir Geri, Rasmus Pagh
Poster
Thu 12:00 Bisection-Based Pricing for Repeated Contextual Auctions against Strategic Buyer
Anton Zhiyanov, Alexey Drutsa
Poster
Thu 12:00 Online Continual Learning from Imbalanced Data
Aristotelis Chrysakis, Marie-Francine Moens
Poster
Thu 12:00 Real-Time Optimisation for Online Learning in Auctions
Lorenzo Croissant, Marc Abeille, Clément Calauzènes
Poster
Thu 12:00 Conditional gradient methods for stochastically constrained convex minimization
Maria Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher
Poster
Thu 12:00 Supervised Quantile Normalization for Low Rank Matrix Factorization
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, JP Vert
Poster
Thu 12:00 On Thompson Sampling with Langevin Algorithms
Eric Mazumdar, Aldo Pacchiano, Yian Ma, Michael Jordan, Peter Bartlett
Poster
Thu 12:00 Online Multi-Kernel Learning with Graph-Structured Feedback
Pouya M Ghari, Yanning Shen
Poster
Thu 12:00 Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi
Poster
Thu 13:00 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Fabian Latorre, Paul Rolland, Shaul Nadav Hallak, Volkan Cevher
Poster
Thu 13:00 The Boomerang Sampler
Joris Bierkens, Sebastiano Grazzi, Kengo Kamatani, Gareth Roberts
Poster
Thu 13:00 On Efficient Low Distortion Ultrametric Embedding
Vincent Cohen-Addad, Karthik C. S., Guillaume Lagarde
Poster
Thu 13:00 The FAST Algorithm for Submodular Maximization
Adam Breuer, Eric Balkanski, Yaron Singer
Poster
Thu 13:00 Preselection Bandits
Viktor Bengs, Eyke Hüllermeier
Poster
Thu 13:00 Amortised Learning by Wake-Sleep
Kevin Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani
Poster
Thu 13:00 Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik
Poster
Thu 13:00 Towards Adaptive Residual Network Training: A Neural-ODE Perspective
Chengyu Dong, Liyuan Liu, Zichao Li, Jingbo Shang
Poster
Thu 14:00 Anderson Acceleration of Proximal Gradient Methods
Vien Mai, Mikael Johansson
Poster
Thu 14:00 Regularized Optimal Transport is Ground Cost Adversarial
François-Pierre Paty, Marco Cuturi
Poster
Thu 14:00 Parallel Algorithm for Non-Monotone DR-Submodular Maximization
Alina Ene, Huy Nguyen
Poster
Thu 14:00 Linear bandits with Stochastic Delayed Feedback
Claire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brueckner
Poster
Thu 14:00 Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Poster
Thu 14:00 Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks
Mark Kurtz, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, Sage Moore, Nir Shavit, Dan Alistarh
Poster
Thu 14:00 Extrapolation for Large-batch Training in Deep Learning
Tao Lin, Lingjing Kong, Sebastian Stich, Martin Jaggi
Poster
Thu 15:00 Off-Policy Actor-Critic with Shared Experience Replay
Simon Schmitt, Matteo Hessel, Karen Simonyan
Poster
Thu 15:00 Learning Factorized Weight Matrix for Joint Filtering
Xiangyu Xu, Yongrui Ma, Wenxiu Sun
Poster
Thu 17:00 Multinomial Logit Bandit with Low Switching Cost
Kefan Dong, Yingkai Li, Qin Zhang, Yuan Zhou
Poster
Thu 17:00 On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes
Naoto Ohsaka, Tatsuya Matsuoka
Poster
Thu 17:00 Sparse Subspace Clustering with Entropy-Norm
Liang Bai, Jiye Liang
Poster
Thu 17:00 Do We Need Zero Training Loss After Achieving Zero Training Error?
Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama
Poster
Thu 17:00 Minimax Weight and Q-Function Learning for Off-Policy Evaluation
Masatoshi Uehara, Jiawei Huang, Nan Jiang
Poster
Thu 17:00 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
Yonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian
Poster
Thu 17:00 Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
Jang-Hyun Kim, Wonho Choo, Hyun Oh Song
Poster
Thu 17:00 Learning Autoencoders with Relational Regularization
Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin
Poster
Thu 17:00 A Graph to Graphs Framework for Retrosynthesis Prediction
Chence Shi, Minkai Xu, Hongyu Guo, Ming Zhang, Jian Tang
Workshop
Thu 23:45 XXAI: Extending Explainable AI Beyond Deep Models and Classifiers
Wojciech Samek, Andreas HOLZINGER, Ruth Fong, Taesup Moon, Klaus-robert Mueller
Workshop
Fri 1:00 5th ICML Workshop on Human Interpretability in Machine Learning (WHI)
Adrian Weller, Alice Xiang, Amit Dhurandhar, Been Kim, Dennis Wei, Kush Varshney, Umang Bhatt
Workshop
Fri 1:30 Law & Machine Learning
Céline Castets-Renard, Sylvain Cussat-Blanc, Laurent Risser
Workshop
Fri 2:00 Analysis of Predictive Coding Models for Phonemic Representation Learning in Small Datasets
María Andrea Cruz Blandón
Workshop
Fri 2:00 Poster session 1
Workshop
Fri 3:30 Healthcare Systems, Population Health, and the Role of Health-tech
Creighton Heaukulani, Konstantina Palla, Katherine Heller, Niranjani Prasad, Marzyeh Ghassemi
Workshop
Fri 4:45 Original Research: Learning Graph Models for Template-Free Retrosynthesis
Vignesh Ram Somnath
Workshop
Fri 5:00 Challenges in Deploying and Monitoring Machine Learning Systems
Alessandra Tosi, Nathan Korda, Neil Lawrence
Workshop
Fri 5:10 Invited Talk: Imputing Missing Data with the Gaussian Copula
Madeleine Udell
Workshop
Fri 6:15 Invited Talk 1 - DeepXML: A Framework for Deep Extreme Multi-label Learning - Manik Varma
Manik Varma
Workshop
Fri 6:30 Exploration, Policy Gradient Methods, and the Deadly Triad - Sham Kakade
Sham Kakade
Workshop
Fri 6:30 Theoretical Foundations of Reinforcement Learning
Emma Brunskill, Thodoris Lykouris, Max Simchowitz, Wen Sun, Mengdi Wang
Workshop
Fri 6:45 What does it mean for ML to be trustworthy?
Nicolas Papernot
Workshop
Fri 6:50 Bridging the gap between research and production in machine learning
Chip Nguyen
Workshop
Fri 7:15 Turning the tables on Facebook: How we audit Facebook using their own marketing tools
Piotr Sapiezynski
Workshop
Fri 7:20 A Unifying View of Optimism in Episodic Reinforcement Learning - Gergely Neu
Gergely Neu
Workshop
Fri 7:30 Uncertainty and Robustness in Deep Learning Workshop (UDL)
Sharon Yixuan Li, Balaji Lakshminarayanan, Dan Hendrycks, Tom Dietterich, Jasper Snoek
Workshop
Fri 7:30 Gradient-Based Monitoring of Learning Machines
Lang Liu
Workshop
Fri 7:45 Talks 2: 5 talks of 15 minutes each
Workshop
Fri 8:35 Invited Talk 4 - Contextual Memory Trees - Alina Beygelzimer
Alina Beygelzimer
Workshop
Fri 9:10 Talk by Francis Bach - Second Order Strikes Back - Globally convergent Newton methods for ill-conditioned generalized self-concordant Losses
Francis Bach
Workshop
Fri 10:40 Conservative Exploration in Bandits and Reinforcement Learning
Mohammad Ghavamzadeh
Workshop
Fri 11:00 Talk by Coralia Cartis - Dimensionality reduction techniques for large-scale optimization problems
Coralia Cartis
Workshop
Fri 11:20 Short Talk 1 - Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
Kwang-Sung Jun
Workshop
Fri 11:35 Short Talk 2 - Adaptive Discretization for Model-Based Reinforcement Learning
Sean Sinclair
Workshop
Fri 11:50 Successful Data Science in Production Systems: It’s All About Assumptions
Nevena Lalic
Workshop
Fri 12:20 Invited Talk: Jeff Clune
Jeff Clune
Workshop
Fri 12:20 Short Talk 5 - Near-Optimal Reinforcement Learning with Self-Play
Tiancheng Yu
Workshop
Fri 12:40 Invited Talk: Feedback in Imitation Learning: Confusion on Causality and Covariate Shift (Arun Venkatraman & Sanjiban Choudhury)
Sanjiban Choudhury, Arun Venkatraman
Workshop
Fri 14:00 Industry Panel - Talk by Boris Ginsburg - Large scale deep learning: new trends and optimization challenges
Boris Ginsburg
Workshop
Fri 14:00 Implicit Neural Scene Representations
Vincent Sitzmann
Workshop
Fri 14:15 Invited Talk 7 - Generalizing to Novel Tasks in the Low-Data Regime - Jure Leskovec
Jure Leskovec
Workshop
Fri 14:20 Representation learning and exploration in reinforcement learning - Akshay Krishnamurthy
Akshay Krishnamurthy
Workshop
Fri 16:00 Efficient Planning in Large MDPs with Weak Linear Function Approximation - Csaba Szepesvari
Csaba Szepesvari
Workshop
Sat 3:00 Inductive Biases, Invariances and Generalization in Reinforcement Learning
Anirudh Goyal, Rosemary Nan Ke, Jane Wang, Theo Weber, Fabio Viola, Bernhard Schölkopf, Stefan Bauer
Workshop
Sat 5:45 Machine Learning for Global Health
Danielle Belgrave, Stephanie Hyland, Charles Onu, Nicholas Furnham, Ernest Mwebaze, Neil Lawrence
Workshop
Sat 5:50 Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
Jian Tang, Le Song, Jure Leskovec, Renjie Liao, Yujia Li, Sanja Fidler, Richard Zemel, Russ Salakhutdinov
Workshop
Sat 6:00 7th ICML Workshop on Automated Machine Learning (AutoML 2020)
Frank Hutter, Joaquin Vanschoren, Marius Lindauer, Charles Weill, Katharina Eggensperger, Matthias Feurer
Workshop
Sat 6:10 Keynote Session 1: Balancing Efficiency and Security in Federated Learning, by Qiang Yang (WeBank)
Qiang Yang
Workshop
Sat 6:25 Ensemble Kernel Methods, Implicit Regularization and Determinantal Point Processes
Joachim Schreurs, Michaël Fanuel, Johan Suykens
Workshop
Sat 7:00 Designing Differentially Private Estimators in High Dimensions by Aditya Dhar
Workshop
Sat 7:15 The NetHack Learning Environment
Tim Rocktäschel
Workshop
Sat 7:45 Negative Dependence and Sampling
Stefanie Jegelka
Workshop
Sat 7:45 Open-ended environments for advancing RL
Max Jaderberg
Workshop
Sat 9:10 Machine Learning for Media Discovery
Erik Schmidt, Oriol Nieto, Fabien Gouyon, Yves Raimond, Katherine Kinnaird, Gert Lanckriet
Workshop
Sat 9:30 Poster session
Workshop
Sat 10:15 Exponentially Faster Algorithms for Machine Learning
Yaron Singer
Workshop
Sat 10:45 Exponentially Faster Algorithms for Machine Learning
Workshop
Sat 11:00 2nd ICML Workshop on Human in the Loop Learning (HILL)
Shanghang Zhang, Xin Wang, Fisher Yu, Jiajun Wu, Prof. Darrell
Workshop
Sat 12:10 Determinantal Point Processes in Randomized Numerical Linear Algebra
Michael Mahoney
Workshop
Sat 12:45 On the Relationship Between Probabilistic Circuits and Determinantal Point Processes
Honghua Zhang, Steven Holtzen, Guy Van den Broeck
Workshop
(#19 / Sess. 1) Neural Bipartite Matching
Dobrik Georgiev
Workshop
Invited Talk: Thwarting Dr. Deceit's Malicious Activities in Conference Peer Review
Nihar Shah
Workshop
Invited Talk: What is my data worth? Towards a Principled and Practical Approach for Data Valuation
Ruoxi Jia
Workshop
(#84 / Sess. 2) UniKER: A Unified Framework for Combining Embedding and Horn Rules for Knowledge Graph Inference
kewei Cheng
Workshop
(#15 / Sess. 2) Learning Distributed Representations of Graphs with Geo2DR
Paul Scherer
Workshop
(#80 / Sess. 2) Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
Christopher Morris
Workshop
(#73 / Sess. 2) Evaluating Logical Generalization in Graph Neural Networks
Koustuv Sinha
Workshop
(#90 / Sess. 1) Pointer Graph Networks
Petar Veličković
Workshop
(#93 / Sess. 1) Geoopt: Riemannian Optimization in PyTorch
Max Kochurov
Workshop
(#96 / Sess. 1) Active Learning on Graphs via Meta Learning
Kaushalya Madhawa