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Expo Workshop
Sun 17:00 PaddlePaddle-based Deep Learning at Baidu
Dejing Dou, Chenxia Li, Teng Xi, Dingfu Zhou, Tianyi Wu, Xuhong Li, Zhengjie Huang, Guocheng Niu, Ji Liu, Yaqing Wang, Xin Wang, Qianwei Cai
Affinity Workshop
Mon 10:50 Generalized linear tree: a flexible algorithm for predicting continuous variables
Alberto Rodrigues Ferreira, Alex Aki Okuno
Tutorial
Mon 12:00 Random Matrix Theory and ML (RMT+ML)
Fabian Pedregosa, Courtney Paquette, Thomas Trogdon, Jeffrey Pennington
Tutorial
Mon 12:00 Online and non-stochastic control
Elad Hazan, Karan Singh
Affinity Workshop
Mon 15:35 Computation-Aware Distributed Optimization over Networks: A Hybrid Dynamical Systems Approach
Daniel Ochoa, Jorge Poveda, Cesar Uribe
Oral Session
Tue 5:00 Optimization (Distributed)
Oral
Tue 5:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
Oral Session
Tue 5:00 Auto-ML and Optimization
Oral
Tue 5:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Oral
Tue 5:00 Phasic Policy Gradient
Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman
Spotlight
Tue 5:20 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Spotlight
Tue 5:20 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Spotlight
Tue 5:25 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
Spotlight
Tue 5:25 Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
Tomoya Murata, Taiji Suzuki
Spotlight
Tue 5:30 Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theo Weber, David Silver, Hado van Hasselt
Spotlight
Tue 5:30 A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization
Ran Xin, Usman Khan, Soummya Kar
Spotlight
Tue 5:30 Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause
Spotlight
Tue 5:35 Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction
Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino
Spotlight
Tue 5:35 Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging
Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud J Rahier
Spotlight
Tue 5:40 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Spotlight
Tue 5:40 Sparsifying Networks via Subdifferential Inclusion
Sagar Verma, Jean-Christophe Pesquet
Spotlight
Tue 5:40 Newton Method over Networks is Fast up to the Statistical Precision
Amir Daneshmand, Gesualdo Scutari, Pavel Dvurechenskii, Alexander Gasnikov
Spotlight
Tue 5:45 Federated Learning under Arbitrary Communication Patterns
Dmitrii Avdiukhin, Shiva Kasiviswanathan
Oral
Tue 6:00 Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
Chaobing Song, Stephen Wright, Jelena Diakonikolas
Oral Session
Tue 6:00 Optimization 1
Oral Session
Tue 6:00 Optimization (Convex) 1
Oral
Tue 6:00 PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik
Spotlight
Tue 6:20 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Spotlight
Tue 6:20 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Spotlight
Tue 6:20 Projection Robust Wasserstein Barycenters
Minhui Huang, Shiqian Ma, Lifeng Lai
Spotlight
Tue 6:25 Efficient Message Passing for 0–1 ILPs with Binary Decision Diagrams
Jan-Hendrik Lange, Paul Swoboda
Spotlight
Tue 6:25 Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
Tolga Ergen, Mert Pilanci
Spotlight
Tue 6:25 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Spotlight
Tue 6:25 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Spotlight
Tue 6:30 Distributionally Robust Optimization with Markovian Data
Mengmeng Li, Tobias Sutter, Daniel Kuhn
Spotlight
Tue 6:30 Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Spotlight
Tue 6:35 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
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 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Spotlight
Tue 6:40 One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
Spotlight
Tue 6:40 A Novel Sequential Coreset Method for Gradient Descent Algorithms
Jiawei Huang, Ruomin Huang, wenjie liu, Nikolaos Freris, Hu Ding
Spotlight
Tue 6:45 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
Oral Session
Tue 7:00 Optimization 2
Oral
Tue 7:00 Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
Vien Mai, Mikael Johansson
Spotlight
Tue 7:20 Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Spotlight
Tue 7:25 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Spotlight
Tue 7:25 Variational Data Assimilation with a Learned Inverse Observation Operator
Thomas Frerix, Dmitrii Kochkov, Jamie Smith, Daniel Cremers, Michael Brenner, Stephan Hoyer
Spotlight
Tue 7:30 Fast Projection Onto Convex Smooth Constraints
Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Levy
Spotlight
Tue 7:35 Decomposable Submodular Function Minimization via Maximum Flow
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu
Spotlight
Tue 7:35 Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell M Aladago, Lorenzo Torresani
Spotlight
Tue 7:40 Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney
Spotlight
Tue 7:45 Distributed Second Order Methods with Fast Rates and Compressed Communication
Rustem Islamov, Xun Qian, Peter Richtarik
Poster
Tue 9:00 Zeroth-Order Non-Convex Learning via Hierarchical Dual Averaging
Amélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud J Rahier
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 On the Optimality of Batch Policy Optimization Algorithms
Chenjun Xiao, Yifan Wu, Jincheng Mei, Bo Dai, Tor Lattimore, Lihong Li, Csaba Szepesvari, Dale Schuurmans
Poster
Tue 9:00 PODS: Policy Optimization via Differentiable Simulation
Miguel Angel Zamora Mora, Momchil Peychev, Sehoon Ha, Martin Vechev, Stelian Coros
Poster
Tue 9:00 One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
Poster
Tue 9:00 Distributed Second Order Methods with Fast Rates and Compressed Communication
Rustem Islamov, Xun Qian, Peter Richtarik
Poster
Tue 9:00 Provably Efficient Learning of Transferable Rewards
Alberto Maria Metelli, Giorgia Ramponi, Alessandro Concetti, Marcello Restelli
Poster
Tue 9:00 ConvexVST: A Convex Optimization Approach to Variance-stabilizing Transformation
Mengfan Wang, Boyu Lyu, Guoqiang Yu
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 Distributionally Robust Optimization with Markovian Data
Mengmeng Li, Tobias Sutter, Daniel Kuhn
Poster
Tue 9:00 Decomposable Submodular Function Minimization via Maximum Flow
Kyriakos Axiotis, Adam Karczmarz, Anish Mukherjee, Piotr Sankowski, Adrian Vladu
Poster
Tue 9:00 Fast Projection Onto Convex Smooth Constraints
Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Levy
Poster
Tue 9:00 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Poster
Tue 9:00 Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell M Aladago, Lorenzo Torresani
Poster
Tue 9:00 Projection Robust Wasserstein Barycenters
Minhui Huang, Shiqian Ma, Lifeng Lai
Poster
Tue 9:00 Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Poster
Tue 9:00 PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik
Poster
Tue 9:00 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Poster
Tue 9:00 Federated Learning under Arbitrary Communication Patterns
Dmitrii Avdiukhin, Shiva Kasiviswanathan
Poster
Tue 9:00 Offline Contextual Bandits with Overparameterized Models
David Brandfonbrener, Will Whitney, Rajesh Ranganath, Joan Bruna
Poster
Tue 9:00 Muesli: Combining Improvements in Policy Optimization
Matteo Hessel, Ivo Danihelka, Fabio Viola, Arthur Guez, Simon Schmitt, Laurent Sifre, Theo Weber, David Silver, Hado van Hasselt
Poster
Tue 9:00 Phasic Policy Gradient
Karl Cobbe, Jacob Hilton, Oleg Klimov, John Schulman
Poster
Tue 9:00 Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
Tolga Ergen, Mert Pilanci
Poster
Tue 9:00 Efficient Message Passing for 0–1 ILPs with Binary Decision Diagrams
Jan-Hendrik Lange, Paul Swoboda
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 Decentralized Riemannian Gradient Descent on the Stiefel Manifold
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Poster
Tue 9:00 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Poster
Tue 9:00 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Poster
Tue 9:00 Multiplicative Noise and Heavy Tails in Stochastic Optimization
Liam Hodgkinson, Michael Mahoney
Poster
Tue 9:00 Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction
Kenta Niwa, Guoqiang Zhang, W. Bastiaan Kleijn, Noboru Harada, Hiroshi Sawada, Akinori Fujino
Poster
Tue 9:00 Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness
Vien Mai, Mikael Johansson
Poster
Tue 9:00 Newton Method over Networks is Fast up to the Statistical Precision
Amir Daneshmand, Gesualdo Scutari, Pavel Dvurechenskii, Alexander Gasnikov
Poster
Tue 9:00 Sparsifying Networks via Subdifferential Inclusion
Sagar Verma, Jean-Christophe Pesquet
Poster
Tue 9:00 Parameter-free Locally Accelerated Conditional Gradients
Alejandro Carderera, Jelena Diakonikolas, Cheuk Yin Lin, Sebastian Pokutta
Poster
Tue 9:00 Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning
Tomoya Murata, Taiji Suzuki
Poster
Tue 9:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Poster
Tue 9:00 Bias-Robust Bayesian Optimization via Dueling Bandits
Johannes Kirschner, Andreas Krause
Poster
Tue 9:00 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
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 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Poster
Tue 9:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
Poster
Tue 9:00 Stochastic Sign Descent Methods: New Algorithms and Better Theory
Mher Safaryan, Peter Richtarik
Poster
Tue 9:00 A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization
Ran Xin, Usman Khan, Soummya Kar
Poster
Tue 9:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Oral Session
Tue 17:00 Optimization and Algorithms 1
Oral
Tue 17:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Oral
Tue 17:00 On the price of explainability for some clustering problems
Eduardo Laber, Lucas Murtinho
Oral Session
Tue 17:00 Optimization 3
Spotlight
Tue 17:20 Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu
Spotlight
Tue 17:20 Instance Specific Approximations for Submodular Maximization
Eric Balkanski, Sharon Qian, Yaron Singer
Spotlight
Tue 17:25 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Spotlight
Tue 17:25 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Spotlight
Tue 17:30 Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien
Spotlight
Tue 17:30 Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Spotlight
Tue 17:30 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Spotlight
Tue 17:40 Stochastic Iterative Graph Matching
Linfeng Liu, Michael Hughes, Soha Hassoun, Liping Liu
Spotlight
Tue 17:40 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Spotlight
Tue 17:45 Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang, Aditya Balu, Ethan Herron, Chinmay Hegde, Soumik Sarkar
Spotlight
Tue 17:45 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Spotlight
Tue 17:45 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Spotlight
Tue 17:45 Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Burak Bartan, Mert Pilanci
Oral
Tue 18:00 Decoupling Value and Policy for Generalization in Reinforcement Learning
Roberta Raileanu, Rob Fergus
Spotlight
Tue 18:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Mohammad Abbasnejad, Reza Haffari
Oral Session
Tue 18:00 Optimization (Stochastic)
Oral
Tue 18:00 Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Oral
Tue 18:00 A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar
Oral
Tue 18:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Oral Session
Tue 18:00 Optimization and Algorithms 2
Oral
Tue 18:00 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein
Spotlight
Tue 18:20 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Spotlight
Tue 18:20 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Spotlight
Tue 18:25 SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Jim Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar
Spotlight
Tue 18:25 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Spotlight
Tue 18:30 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Spotlight
Tue 18:30 Communication-Efficient Distributed SVD via Local Power Iterations
Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang
Spotlight
Tue 18:30 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
Spotlight
Tue 18:35 Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge
Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Levy
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 18:35 Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng
Spotlight
Tue 18:40 Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Yorgos Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser
Spotlight
Tue 18:40 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
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 18:45 Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard Lewis, Satinder Singh
Spotlight
Tue 18:45 CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
Anselm Paulus, Michal Rolinek, Vit Musil, Brandon Amos, Georg Martius
Oral Session
Tue 19:00 Optimization (Convex) 2
Oral
Tue 19:00 Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm
TaeHo Yoon, Ernest Ryu
Oral
Tue 19:00 Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen
Oral
Tue 19:00 Just Train Twice: Improving Group Robustness without Training Group Information
Evan Liu, Behzad Haghgoo, Annie Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Oral
Tue 19:00 Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Jörn Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville
Oral Session
Tue 19:00 Optimization 4
Oral Session
Tue 19:00 Large Scale Optimization
Spotlight
Tue 19:20 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Spotlight
Tue 19:20 Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers
Jyotikrishna Dass, Rabi Mahapatra
Spotlight
Tue 19:20 Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi
Spotlight
Tue 19:20 Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
Spotlight
Tue 19:20 A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
Scott Fujimoto, David Meger, Doina Precup
Spotlight
Tue 19:20 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Spotlight
Tue 19:25 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Spotlight
Tue 19:25 Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks
Huiping Zhuang, Zhenyu Weng, Fulin Luo, Kar-Ann Toh, Haizhou Li, Zhiping Lin
Spotlight
Tue 19:25 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Spotlight
Tue 19:25 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Spotlight
Tue 19:25 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
Spotlight
Tue 19:25 Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
Spotlight
Tue 19:30 Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
Radu Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx
Spotlight
Tue 19:30 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
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 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Spotlight
Tue 19:35 Moreau-Yosida $f$-divergences
Dávid Terjék
Spotlight
Tue 19:35 1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
Spotlight
Tue 19:40 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Spotlight
Tue 19:40 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Spotlight
Tue 19:40 Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur
Spotlight
Tue 19:40 Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul G. Krishnan, David Sontag
Spotlight
Tue 19:40 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
Spotlight
Tue 19:40 Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization
Neha Wadia, Daniel Duckworth, Samuel Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein
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 Three Operator Splitting with a Nonconvex Loss Function
Alp Yurtsever, Varun Mangalick, Suvrit Sra
Spotlight
Tue 19:45 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Poster
Tue 21:00 Discovering symbolic policies with deep reinforcement learning
Mikel Landajuela Larma, Brenden Petersen, Sookyung Kim, Claudio Santiago, Ruben Glatt, Nathan Mundhenk, Jacob Pettit, Daniel Faissol
Poster
Tue 21:00 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
Poster
Tue 21:00 A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
Scott Fujimoto, David Meger, Doina Precup
Poster
Tue 21:00 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein
Poster
Tue 21:00 Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge
Rotem Zamir Aviv, Ido Hakimi, Assaf Schuster, Kfir Levy
Poster
Tue 21:00 Taylor Expansion of Discount Factors
Yunhao Tang, Mark Rowland, Remi Munos, Michal Valko
Poster
Tue 21:00 On Estimation in Latent Variable Models
Guanhua Fang, Ping Li
Poster
Tue 21:00 Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning
Hiroki Furuta, Tatsuya Matsushima, Tadashi Kozuno, Yutaka Matsuo, Sergey Levine, Ofir Nachum, Shixiang Gu
Poster
Tue 21:00 Communication-Efficient Distributed Optimization with Quantized Preconditioners
Foivos Alimisis, Peter Davies, Dan Alistarh
Poster
Tue 21:00 Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi
Poster
Tue 21:00 Communication-Efficient Distributed SVD via Local Power Iterations
Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang
Poster
Tue 21:00 Regularized Submodular Maximization at Scale
Ehsan Kazemi, shervin minaee, Moran Feldman, Amin Karbasi
Poster
Tue 21:00 Whitening and Second Order Optimization Both Make Information in the Dataset Unusable During Training, and Can Reduce or Prevent Generalization
Neha Wadia, Daniel Duckworth, Samuel Schoenholz, Ethan Dyer, Jascha Sohl-Dickstein
Poster
Tue 21:00 Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen
Poster
Tue 21:00 Rethinking Neural vs. Matrix-Factorization Collaborative Filtering: the Theoretical Perspectives
Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, Kannan Achan
Poster
Tue 21:00 BASGD: Buffered Asynchronous SGD for Byzantine Learning
Yi-Rui Yang, Wu-Jun Li
Poster
Tue 21:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Mohammad Abbasnejad, Reza Haffari
Poster
Tue 21:00 On the price of explainability for some clustering problems
Eduardo Laber, Lucas Murtinho
Poster
Tue 21:00 A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina Eldar, Alireza Fallah, Farzan Farnia, Asuman Ozdaglar
Poster
Tue 21:00 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
Poster
Tue 21:00 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Poster
Tue 21:00 Accumulated Decoupled Learning with Gradient Staleness Mitigation for Convolutional Neural Networks
Huiping Zhuang, Zhenyu Weng, Fulin Luo, Kar-Ann Toh, Haizhou Li, Zhiping Lin
Poster
Tue 21:00 Instance Specific Approximations for Submodular Maximization
Eric Balkanski, Sharon Qian, Yaron Singer
Poster
Tue 21:00 Accelerate CNNs from Three Dimensions: A Comprehensive Pruning Framework
Wenxiao Wang, Minghao Chen, Shuai Zhao, Long Chen, Jinming Hu, Haifeng Liu, Deng Cai, Xiaofei He, Wei Liu
Poster
Tue 21:00 Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Mehdi Fatemi, Honglak Lee
Poster
Tue 21:00 The Power of Adaptivity for Stochastic Submodular Cover
Rohan Ghuge, Anupam Gupta, viswanath nagarajan
Poster
Tue 21:00 Oblivious Sketching-based Central Path Method for Linear Programming
Zhao Song, Zheng Yu
Poster
Tue 21:00 Just Train Twice: Improving Group Robustness without Training Group Information
Evan Liu, Behzad Haghgoo, Annie Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Poster
Tue 21:00 On Proximal Policy Optimization's Heavy-tailed Gradients
Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Russ Salakhutdinov, Pradeep Ravikumar
Poster
Tue 21:00 Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien
Poster
Tue 21:00 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Poster
Tue 21:00 Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Jörn Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville
Poster
Tue 21:00 Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
Yorgos Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti-Spaccamela, Rebecca Reiffenhäuser
Poster
Tue 21:00 Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique, Paul Weng
Poster
Tue 21:00 Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Burak Bartan, Mert Pilanci
Poster
Tue 21:00 SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies
Jim Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar
Poster
Tue 21:00 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Poster
Tue 21:00 Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
Shariq Iqbal, Christian Schroeder, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha
Poster
Tue 21:00 Randomized Algorithms for Submodular Function Maximization with a $k$-System Constraint
Shuang Cui, Kai Han, Tianshuai Zhu, Jing Tang, Benwei Wu, He Huang
Poster
Tue 21:00 Learning While Playing in Mean-Field Games: Convergence and Optimality
Qiaomin Xie, Zhuoran Yang, Zhaoran Wang, Andreea Minca
Poster
Tue 21:00 Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers
Jyotikrishna Dass, Rabi Mahapatra
Poster
Tue 21:00 Federated Composite Optimization
Honglin Yuan, Manzil Zaheer, Sashank Jakkam Reddi
Poster
Tue 21:00 Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
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 Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
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 CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
Anselm Paulus, Michal Rolinek, Vit Musil, Brandon Amos, Georg Martius
Poster
Tue 21:00 Reinforcement Learning of Implicit and Explicit Control Flow Instructions
Ethan Brooks, Janarthanan Rajendran, Richard Lewis, Satinder Singh
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 SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II
Xiangjun Wang, Junxiao SONG, Penghui Qi, Peng Peng, Zhenkun Tang, Wei Zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao Gao, Haitao Long, Quan Yuan
Poster
Tue 21:00 Representation Matters: Offline Pretraining for Sequential Decision Making
Mengjiao Yang, Ofir Nachum
Poster
Tue 21:00 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Poster
Tue 21:00 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Poster
Tue 21:00 Moreau-Yosida $f$-divergences
Dávid Terjék
Poster
Tue 21:00 Three Operator Splitting with a Nonconvex Loss Function
Alp Yurtsever, Varun Mangalick, Suvrit Sra
Poster
Tue 21:00 Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wes Chung, Valentin Thomas, Marlos C. Machado, Nicolas Le Roux
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 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Poster
Tue 21:00 Monotonic Robust Policy Optimization with Model Discrepancy
yuankun jiang, Chenglin Li, Wenrui Dai, Junni Zou, Hongkai Xiong
Poster
Tue 21:00 1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
Poster
Tue 21:00 Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien, Damien Scieur
Poster
Tue 21:00 Accelerated Algorithms for Smooth Convex-Concave Minimax Problems with O(1/k^2) Rate on Squared Gradient Norm
TaeHo Yoon, Ernest Ryu
Poster
Tue 21:00 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Poster
Tue 21:00 Stochastic Iterative Graph Matching
Linfeng Liu, Michael Hughes, Soha Hassoun, Liping Liu
Poster
Tue 21:00 On a Combination of Alternating Minimization and Nesterov's Momentum
Sergey Guminov, Pavel Dvurechenskii, Nazarii Tupitsa, Alexander Gasnikov
Oral
Wed 5:00 When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
Oral
Wed 5:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Oral Session
Wed 5:00 Optimization (Nonconvex)
Oral
Wed 5:00 Optimizing persistent homology based functions
Mathieu Carrière, Frederic Chazal, Marc Glisse, Yuichi Ike, Hariprasad Kannan, Yuhei Umeda
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 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Spotlight
Wed 5:25 SMG: A Shuffling Gradient-Based Method with Momentum
Trang Tran, Lam Nguyen, Quoc Tran-Dinh
Spotlight
Wed 5:25 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
Spotlight
Wed 5:30 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach
Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher
Spotlight
Wed 5:30 Estimating $\alpha$-Rank from A Few Entries with Low Rank Matrix Completion
Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang
Spotlight
Wed 5:30 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Spotlight
Wed 5:35 MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtarik
Spotlight
Wed 5:40 Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi
Spotlight
Wed 5:40 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Spotlight
Wed 5:45 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 5:45 Learning from History for Byzantine Robust Optimization
Praneeth Karimireddy, Lie He, Martin Jaggi
Spotlight
Wed 5:45 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
Spotlight
Wed 5:45 Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller
Oral
Wed 6:00 Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson
Oral
Wed 6:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Oral
Wed 6:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Oral
Wed 6:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Oral
Wed 6:00 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Oral Session
Wed 6:00 Optimization and Algorithms 3
Oral Session
Wed 6:00 Reinforcement Learning and Optimization
Spotlight
Wed 6:25 A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, Jake Abernethy
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 Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig
Spotlight
Wed 6:30 Online A-Optimal Design and Active Linear Regression
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
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 6:35 Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
Yun Kuen Cheung, Georgios Piliouras
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 6:40 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Spotlight
Wed 6:40 TempoRL: Learning When to Act
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
Spotlight
Wed 6:45 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Oral
Wed 7:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Oral
Wed 7:00 Kernel Stein Discrepancy Descent
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Spotlight
Wed 7:20 Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren
Spotlight
Wed 7:30 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Spotlight
Wed 7:30 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 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
Spotlight
Wed 7:40 Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li
Spotlight
Wed 7:40 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Spotlight
Wed 7:45 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Spotlight
Wed 7:45 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Spotlight
Wed 7:45 Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg
Poster
Wed 9:00 Meta-learning Hyperparameter Performance Prediction with Neural Processes
Ying WEI, Peilin Zhao, Junzhou Huang
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 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 TempoRL: Learning When to Act
André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
Poster
Wed 9:00 Dichotomous Optimistic Search to Quantify Human Perception
Julien Audiffren
Poster
Wed 9:00 Regret Minimization in Stochastic Non-Convex Learning via a Proximal-Gradient Approach
Nadav Hallak, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 9:00 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye, Zhaoran Wang, Zhuoran Yang
Poster
Wed 9:00 MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard Gorbunov, Konstantin Burlachenko, Zhize Li, Peter Richtarik
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 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 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Poster
Wed 9:00 Learning from History for Byzantine Robust Optimization
Praneeth Karimireddy, Lie He, Martin Jaggi
Poster
Wed 9:00 Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li
Poster
Wed 9:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl Johansson
Poster
Wed 9:00 Adversarial Combinatorial Bandits with General Non-linear Reward Functions
Yanjun Han, Yining Wang, Xi Chen
Poster
Wed 9:00 Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji, Junjie Yang, Yingbin LIANG
Poster
Wed 9:00 Guided Exploration with Proximal Policy Optimization using a Single Demonstration
Gabriele Libardi, Gianni De Fabritiis, Sebastian Dittert
Poster
Wed 9:00 Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak, Mingchen Li, Mahdi Soltanolkotabi
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 Efficient Performance Bounds for Primal-Dual Reinforcement Learning from Demonstrations
Angeliki Kamoutsi, Goran Banjac, John Lygeros
Poster
Wed 9:00 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Poster
Wed 9:00 Kernel Stein Discrepancy Descent
Anna Korba, Pierre-Cyril Aubin-Frankowski, Szymon Majewski, Pierre Ablin
Poster
Wed 9:00 Reserve Price Optimization for First Price Auctions in Display Advertising
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
Poster
Wed 9:00 SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao YANG, Ru-Yuan Zhang, Lida LI, Xiaohua Xie
Poster
Wed 9:00 Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
Yun Kuen Cheung, Georgios Piliouras
Poster
Wed 9:00 Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
Hedda Cohen Indelman, Tamir Hazan
Poster
Wed 9:00 Value Iteration in Continuous Actions, States and Time
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg
Poster
Wed 9:00 Estimating $\alpha$-Rank from A Few Entries with Low Rank Matrix Completion
Yali Du, Xue Yan, Xu Chen, Jun Wang, Haifeng Zhang
Poster
Wed 9:00 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Poster
Wed 9:00 Online A-Optimal Design and Active Linear Regression
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
Poster
Wed 9:00 Guarantees for Tuning the Step Size using a Learning-to-Learn Approach
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge
Poster
Wed 9:00 When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao, Qingming Huang
Poster
Wed 9:00 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Poster
Wed 9:00 Multiplying Matrices Without Multiplying
Davis Blalock, John Guttag
Poster
Wed 9:00 A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, Jake Abernethy
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 SMG: A Shuffling Gradient-Based Method with Momentum
Trang Tran, Lam Nguyen, Quoc Tran-Dinh
Poster
Wed 9:00 Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig
Poster
Wed 9:00 Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning
Sebastian Curi, Ilija Bogunovic, Andreas Krause
Poster
Wed 9:00 Inferring serial correlation with dynamic backgrounds
Song Wei, Yao Xie, Dobromir Rahnev
Poster
Wed 9:00 The Limits of Min-Max Optimization Algorithms: Convergence to Spurious Non-Critical Sets
Ya-Ping Hsieh, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 9:00 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Poster
Wed 9:00 Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala Bukkapatnam, Noah Siegel, Nicolas Heess, Martin Riedmiller
Oral
Wed 17:00 Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah
Oral
Wed 17:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Oral Session
Wed 17:00 Deep Learning Optimization
Oral
Wed 17:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Spotlight
Wed 17:20 Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions
Pierre Alquier
Spotlight
Wed 17:20 Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
Spotlight
Wed 17:25 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Spotlight
Wed 17:30 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Spotlight
Wed 17:30 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Spotlight
Wed 17:30 Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Spotlight
Wed 17:35 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras
Spotlight
Wed 17:35 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Spotlight
Wed 17:35 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
Spotlight
Wed 17:35 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Spotlight
Wed 17:40 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Spotlight
Wed 17:40 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Spotlight
Wed 17:45 Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin Haeffele, Rene Vidal
Spotlight
Wed 17:45 Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Oral
Wed 18:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Spotlight
Wed 18:20 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Spotlight
Wed 18:20 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Spotlight
Wed 18:20 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
Syama Sundar Yadav Rangapuram, Lucien Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
Spotlight
Wed 18:25 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Spotlight
Wed 18:35 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Spotlight
Wed 18:40 A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee, Ali S. Mazloom, Giridhar Kaushik , Kookjin Lee, Noseong Park
Spotlight
Wed 18:45 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Oral
Wed 19:00 Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
Spotlight
Wed 19:20 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 DORO: Distributional and Outlier Robust Optimization
Runtian Zhai, Chen Dan, Zico Kolter, Pradeep Ravikumar
Spotlight
Wed 19:30 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Spotlight
Wed 19:30 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Spotlight
Wed 19:35 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
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 Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis
Spotlight
Wed 19:40 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
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 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras
Poster
Wed 21:00 Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Poster
Wed 21:00 Approximation Theory Based Methods for RKHS Bandits
Sho Takemori, Masahiro Sato
Poster
Wed 21:00 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Poster
Wed 21:00 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
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 Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
Yifang Chen, Simon Du, Kevin Jamieson
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 Non-Exponentially Weighted Aggregation: Regret Bounds for Unbounded Loss Functions
Pierre Alquier
Poster
Wed 21:00 Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
Poster
Wed 21:00 DORO: Distributional and Outlier Robust Optimization
Runtian Zhai, Chen Dan, Zico Kolter, Pradeep Ravikumar
Poster
Wed 21:00 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Poster
Wed 21:00 Outside the Echo Chamber: Optimizing the Performative Risk
John Miller, Juan Perdomo, Tijana Zrnic
Poster
Wed 21:00 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Poster
Wed 21:00 Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning
Hassan Hafez-Kolahi, Behrad Moniri, Shohreh Kasaei, Mahdieh Soleymani Baghshah
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 Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Poster
Wed 21:00 Leveraging Non-uniformity in First-order Non-convex Optimization
Jincheng Mei, Yue Gao, Bo Dai, Csaba Szepesvari, Dale Schuurmans
Poster
Wed 21:00 Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality
Jonathan Lacotte, Yifei Wang, Mert Pilanci
Poster
Wed 21:00 Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin Haeffele, Rene Vidal
Poster
Wed 21:00 Implicit rate-constrained optimization of non-decomposable objectives
Abhishek Kumar, Harikrishna Narasimhan, Andrew Cotter
Poster
Wed 21:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Poster
Wed 21:00 Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Poster
Wed 21:00 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport
Lewis Liu, Yufeng Zhang, Zhuoran Yang, Reza Babanezhad, Zhaoran Wang
Poster
Wed 21:00 Versatile Verification of Tree Ensembles
Laurens Devos, Wannes Meert, Jesse Davis
Poster
Wed 21:00 End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series
Syama Sundar Yadav Rangapuram, Lucien Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski
Poster
Wed 21:00 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Poster
Wed 21:00 Train simultaneously, generalize better: Stability of gradient-based minimax learners
Farzan Farnia, Asuman Ozdaglar
Poster
Wed 21:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Poster
Wed 21:00 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Poster
Wed 21:00 On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks
Hancheng Min, Salma Tarmoun, Rene Vidal, Enrique Mallada
Poster
Wed 21:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Poster
Wed 21:00 A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee, Ali S. Mazloom, Giridhar Kaushik , Kookjin Lee, Noseong Park
Oral
Thu 5:00 Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Spotlight
Thu 5:20 DAGs with No Curl: An Efficient DAG Structure Learning Approach
Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji
Spotlight
Thu 5:25 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
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 5:40 Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Zolna
Spotlight
Thu 5:45 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Spotlight
Thu 5:45 A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio Mayrink Verdun
Spotlight
Thu 5:45 Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Spotlight
Thu 5:45 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Oral
Thu 6:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Oral
Thu 6:00 Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, rong jin
Spotlight
Thu 6:20 Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Spotlight
Thu 6:20 Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design
Gustavo Malkomes, Harvey Cheng, Eric Lee, Michael McCourt
Spotlight
Thu 6:25 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Spotlight
Thu 6:25 Nondeterminism and Instability in Neural Network Optimization
Cecilia Summers, Michael J Dinneen
Spotlight
Thu 6:30 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
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 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Spotlight
Thu 6:35 Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein
Spotlight
Thu 6:35 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi
Spotlight
Thu 6:40 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Spotlight
Thu 6:40 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Spotlight
Thu 6:40 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Spotlight
Thu 6:40 Conservative Objective Models for Effective Offline Model-Based Optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
Spotlight
Thu 6:40 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Spotlight
Thu 6:45 Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron Wagner, Jayadev Acharya
Spotlight
Thu 6:45 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Oral
Thu 7:00 Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang
Spotlight
Thu 7:25 Parallel tempering on optimized paths
Saif Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Côté
Spotlight
Thu 7:25 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Spotlight
Thu 7:25 SketchEmbedNet: Learning Novel Concepts by Imitating Drawings
Alexander Wang, Mengye Ren, Richard Zemel
Spotlight
Thu 7:35 Matrix Completion with Model-free Weighting
Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan
Spotlight
Thu 7:40 Environment Inference for Invariant Learning
Elliot Creager, Jörn Jacobsen, Richard Zemel
Spotlight
Thu 7:40 Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Spotlight
Thu 7:45 A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization
Andrew Campbell, Wenlong Chen, Vincent Stimper, Jose Miguel Hernandez-Lobato, Yichuan Zhang
Poster
Thu 9:00 Graph Contrastive Learning Automated
Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang
Poster
Thu 9:00 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Poster
Thu 9:00 Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Poster
Thu 9:00 Feature Clustering for Support Identification in Extreme Regions
Hamid Jalalzai, Rémi Leluc
Poster
Thu 9:00 Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Adrien Corenflos, James Thornton, George Deligiannidis, Arnaud Doucet
Poster
Thu 9:00 Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron Wagner, Jayadev Acharya
Poster
Thu 9:00 SketchEmbedNet: Learning Novel Concepts by Imitating Drawings
Alexander Wang, Mengye Ren, Richard Zemel
Poster
Thu 9:00 Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
Poster
Thu 9:00 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Poster
Thu 9:00 Optimization Planning for 3D ConvNets
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Tao Mei
Poster
Thu 9:00 DAGs with No Curl: An Efficient DAG Structure Learning Approach
Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji
Poster
Thu 9:00 Beyond the Pareto Efficient Frontier: Constraint Active Search for Multiobjective Experimental Design
Gustavo Malkomes, Harvey Cheng, Eric Lee, Michael McCourt
Poster
Thu 9:00 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
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 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Poster
Thu 9:00 Bayesian Quadrature on Riemannian Data Manifolds
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Poster
Thu 9:00 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Poster
Thu 9:00 Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola
Poster
Thu 9:00 Robust Learning-Augmented Caching: An Experimental Study
Jakub Chłędowski, Adam Polak, Bartosz Szabucki, Konrad Zolna
Poster
Thu 9:00 Matrix Completion with Model-free Weighting
Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan
Poster
Thu 9:00 A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization
Andrew Campbell, Wenlong Chen, Vincent Stimper, Jose Miguel Hernandez-Lobato, Yichuan Zhang
Poster
Thu 9:00 Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling
Ozan Özdenizci, Robert Legenstein
Poster
Thu 9:00 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Poster
Thu 9:00 Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye, Qi Qian, Yufeng Li, Baigui Sun, Hao Li, rong jin
Poster
Thu 9:00 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
Poster
Thu 9:00 Improved, Deterministic Smoothing for L_1 Certified Robustness
Alexander Levine, Soheil Feizi
Poster
Thu 9:00 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Poster
Thu 9:00 A Scalable Second Order Method for Ill-Conditioned Matrix Completion from Few Samples
Christian Kümmerle, Claudio Mayrink Verdun
Poster
Thu 9:00 Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
Willie Neiswanger, Ke Alexander Wang, Stefano Ermon
Poster
Thu 9:00 Parallel tempering on optimized paths
Saif Syed, Vittorio Romaniello, Trevor Campbell, Alexandre Bouchard-Côté
Poster
Thu 9:00 Conservative Objective Models for Effective Offline Model-Based Optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
Poster
Thu 9:00 Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni, Marco Lorenzi
Poster
Thu 9:00 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Poster
Thu 9:00 Nondeterminism and Instability in Neural Network Optimization
Cecilia Summers, Michael J Dinneen
Poster
Thu 9:00 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Poster
Thu 9:00 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Poster
Thu 9:00 Environment Inference for Invariant Learning
Elliot Creager, Jörn Jacobsen, Richard Zemel
Oral
Thu 17:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Spotlight
Thu 17:20 Objective Bound Conditional Gaussian Process for Bayesian Optimization
Taewon Jeong, Heeyoung Kim
Spotlight
Thu 17:20 Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li
Spotlight
Thu 17:35 Bias-Free Scalable Gaussian Processes via Randomized Truncations
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John Cunningham
Spotlight
Thu 17:35 Large-Scale Meta-Learning with Continual Trajectory Shifting
JWoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
Spotlight
Thu 17:35 Towards Better Robust Generalization with Shift Consistency Regularization
Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi
Spotlight
Thu 17:45 A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
HanQin Cai, Yuchen Lou, Daniel Mckenzie, Wotao Yin
Spotlight
Thu 18:25 Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig
Spotlight
Thu 18:25 Improving Predictors via Combination Across Diverse Task Categories
Kwang In Kim
Spotlight
Thu 18:25 Breaking the Deadly Triad with a Target Network
Shangtong Zhang, Hengshuai Yao, Shimon Whiteson
Spotlight
Thu 18:35 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
Spotlight
Thu 18:40 Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan
Spotlight
Thu 18:40 Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada
Spotlight
Thu 18:40 Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method
Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So
Spotlight
Thu 18:40 Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li
Spotlight
Thu 19:05 Neural Tangent Generalization Attacks
Jimmy Yuan, Shan-Hung (Brandon) Wu
Spotlight
Thu 19:20 A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao
Spotlight
Thu 19:25 Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
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 19:30 Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
Spotlight
Thu 19:40 Active Learning for Distributionally Robust Level-Set Estimation
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
Spotlight
Thu 19:40 Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations
Mateusz Wilinski, Andrey Lokhov
Spotlight
Thu 19:45 Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel Robinson
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 Optimization 6
Spotlight
Thu 20:30 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Spotlight Session
Thu 20:30 Optimization 5
Spotlight
Thu 20:30 Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
Spotlight
Thu 20:30 Lenient Regret and Good-Action Identification in Gaussian Process Bandits
Xu Cai, Selwyn Gomes, Jonathan Scarlett
Spotlight
Thu 20:35 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Spotlight
Thu 20:35 Fast margin maximization via dual acceleration
Ziwei Ji, Nati Srebro, Matus Telgarsky
Spotlight
Thu 20:35 ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Alexander Rogozin, Alexander Gasnikov
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 A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona
Spotlight
Thu 20:40 ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi
Spotlight
Thu 20:45 Learner-Private Convex Optimization
Jiaming Xu, Kuang Xu, Dana Yang
Spotlight
Thu 20:45 High-Dimensional Gaussian Process Inference with Derivatives
Filip de Roos, Alexandra Gessner, Philipp Hennig
Spotlight
Thu 20:45 A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
Spotlight
Thu 20:50 Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
Spotlight
Thu 20:50 Learn2Hop: Learned Optimization on Rough Landscapes
Amil Merchant, Luke Metz, Samuel Schoenholz, Ekin Dogus Cubuk
Poster
Thu 21:00 Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method
Peng Wang, Huikang Liu, Zirui Zhou, Anthony Man-Cho So
Poster
Thu 21:00 ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi
Poster
Thu 21:00 Large-Scale Meta-Learning with Continual Trajectory Shifting
JWoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
Poster
Thu 21:00 Dual Principal Component Pursuit for Robust Subspace Learning: Theory and Algorithms for a Holistic Approach
Tianyu Ding, Zhihui Zhu, Rene Vidal, Daniel Robinson
Poster
Thu 21:00 Prediction-Centric Learning of Independent Cascade Dynamics from Partial Observations
Mateusz Wilinski, Andrey Lokhov
Poster
Thu 21:00 Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
Poster
Thu 21:00 Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan
Poster
Thu 21:00 A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
HanQin Cai, Yuchen Lou, Daniel Mckenzie, Wotao Yin
Poster
Thu 21:00 Towards Better Robust Generalization with Shift Consistency Regularization
Shufei Zhang, Zhuang Qian, Kaizhu Huang, Qiufeng Wang, Rui Zhang, Xinping Yi
Poster
Thu 21:00 Learn2Hop: Learned Optimization on Rough Landscapes
Amil Merchant, Luke Metz, Samuel Schoenholz, Ekin Dogus Cubuk
Poster
Thu 21:00 Improving Predictors via Combination Across Diverse Task Categories
Kwang In Kim
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 Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
Poster
Thu 21:00 Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li
Poster
Thu 21:00 Active Learning for Distributionally Robust Level-Set Estimation
Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi
Poster
Thu 21:00 Learner-Private Convex Optimization
Jiaming Xu, Kuang Xu, Dana Yang
Poster
Thu 21:00 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
Poster
Thu 21:00 Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
Poster
Thu 21:00 A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona
Poster
Thu 21:00 Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul G. Krishnan, David Sontag
Poster
Thu 21:00 A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
Poster
Thu 21:00 High-Dimensional Gaussian Process Inference with Derivatives
Filip de Roos, Alexandra Gessner, Philipp Hennig
Poster
Thu 21:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
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 A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao
Poster
Thu 21:00 Objective Bound Conditional Gaussian Process for Bayesian Optimization
Taewon Jeong, Heeyoung Kim
Poster
Thu 21:00 Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
Poster
Thu 21:00 ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
Dmitry Kovalev, Egor Shulgin, Peter Richtarik, Alexander Rogozin, Alexander Gasnikov
Poster
Thu 21:00 Neural Tangent Generalization Attacks
Jimmy Yuan, Shan-Hung (Brandon) Wu
Poster
Thu 21:00 Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
Poster
Thu 21:00 On Lower Bounds for Standard and Robust Gaussian Process Bandit Optimization
Xu Cai, Jonathan Scarlett
Poster
Thu 21:00 Lenient Regret and Good-Action Identification in Gaussian Process Bandits
Xu Cai, Selwyn Gomes, Jonathan Scarlett
Poster
Thu 21:00 Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li
Poster
Thu 21:00 Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada
Poster
Thu 21:00 Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig
Poster
Thu 21:00 Bias-Free Scalable Gaussian Processes via Randomized Truncations
Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, John Cunningham
Poster
Thu 21:00 Fast margin maximization via dual acceleration
Ziwei Ji, Nati Srebro, Matus Telgarsky
Workshop
Fri 4:40 Machine Learning for Chip Design
Roberto Bondesan
Workshop
Fri 6:00 8th ICML Workshop on Automated Machine Learning (AutoML 2021)
Gresa Shala, Frank Hutter, Joaquin Vanschoren, Marius Lindauer, Katharina Eggensperger, Colin White, Erin LeDell
Workshop
Fri 6:46 Invited Talk by Ellen Vitercik: Automated Parameter Optimization for Integer Programming
Ellen Vitercik
Workshop
Fri 7:26 Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization
David Eriksson
Workshop
Fri 7:28 Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization
Akihiro Kishimoto
Workshop
Fri 7:32 Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance
Pari Ram
Workshop
Fri 7:33 Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization
Thomas Elsken, Difan Deng
Workshop
Fri 7:35 Towards Explaining Hyperparameter Optimization via Partial Dependence Plots
Julia Moosbauer, Julia Herbinger
Workshop
Fri 7:36 Mutation is all you need
Lennart Schneider
Workshop
Fri 9:46 LRTuner: A Learning Rate Tuner for Deep Neural Networks
Nipun Kwatra
Workshop
Fri 9:48 Replacing the Ex-Def Baseline in AutoML by Naive AutoML
Felix Mohr
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 10:40 Contributed Talks Session 2
Saeed Sharifi-Malvajerdi, Audra McMillan, Ryan McKenna
Workshop
Fri 11:45 Improving Robustness to Distribution Shifts: Methods and Benchmarks
Shiori Sagawa
Workshop
Sat 5:30 Berk Ustun - On Predictions without Recourse
Workshop
Sat 6:55 CounterNet: End-to-End Training of Counterfactual Aware Predictions
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 7:30 Data Summarization via Bilevel Coresets
Andreas Krause
Workshop
Sat 8:05 Conjugate gradient techniques for nonconvex optimization
Clément Royer
Workshop
Sat 8:40 Highlight 5 | Data-driven Experimental Prioritization via Imputation and Submodular Optimization
Workshop CompBio, Jacob Schreiber
Workshop
Sat 9:20 Algorithms for Deterministically Constrained Stochastic Optimization
Frank E Curtis
Workshop
Sat 9:30 Invited Speaker: Christian Kroer: Recent Advances in Iterative Methods for Large-Scale Game Solving
Christian Kroer
Workshop
Sat 10:00 The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning
Mikhail Belkin
Workshop
Sat 10:30 Benchmarks and Toolkits for Data Subset Selection in ML through DECILE: Part I
Rishabh Lyer
Workshop
Sat 10:44 Benchmarks and Toolkits for Data Subset Selection in ML through DECILE: Part II
Ganesh Ramakrishnan
Workshop
Sat 11:45 Morning Poster Session: Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators.
Victor Storchan, Svitlana Vyetrenko
Workshop
Sat 11:45 Morning Poster Session: Revisiting Dynamic Regret of Strongly Adaptive Methods
Dheeraj Baby
Workshop
Sat 12:00 Online and Non Parametric Coresets for Bregman Divergence
Supratim Shit, Rachit Chhaya, Anirban Dasgupta, Jayesh Choudhari
Workshop
Sat 12:23 Selective Focusing Learning in Conditional GANs
Kyeongbo Kong, Kyunghun Kim, Woo-jin Song, Suk-Ju Kang
Workshop
Sat 12:30 Optimization Aspects of Personalized Federated Learning
Filip Hanzely
Workshop
Sat 12:55 Optimization Aspects of Personalized Federated Learning (Q&A)
Filip Hanzely
Workshop
Sat 13:00 Descent method framework in optimization
Ashia Wilson
Workshop
Sat 13:02 Sparse Bayesian Learning via Stepwise Regression
Sebastian Ament, Carla Gomes
Workshop
Sat 13:07 Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, Woo-jin Song
Workshop
Sat 13:55 Faster Empirical Risk Minimization
Jelena Diakonikolas
Workshop
Sat 15:35 Implicit Regularization in Overparameterized Bilevel Optimization
Paul Vicol
Workshop
Sat 15:45 CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Workshop
Sat 15:45 Stochastic Variance-Reduced High-order Optimization for Nonconvex Optimization
Quanquan Gu
Workshop
Sat 15:55 Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Workshop
Sat 15:55 Universal Prediction Band, Semi-Definite Programming and Variance Interpolation
Tengyuan Liang
Workshop
Sat 15:59 Improved Regret Bounds for Online Submodular Maximization
Omid Sadeghi, Maryam Fazel
Workshop
Sat 16:09 Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga S, Ganesh Ramakrishnan, Rishabh Lyer
Workshop
Sat 16:19 Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity
Praneeth Vepakomma, Ramesh Raskar
Workshop
Sat 17:00 Afternoon Poster Session: Robust Price Optimization in Retail
Linsey Pang
Workshop
Sat 17:45 Robust Validation: Confident Predictions Even When Distributions Shift (Spotlight #11)
Suyash Gupta
Workshop
Sat 18:03 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning (Spotlight #13)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Workshop
Learning with User-Level Privacy
Daniel A Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh
Workshop
Prior-Aware Distribution Estimation for Differential Privacy
Yuchao Tao, Johes Bater, Ashwin Machanavajjhala
Workshop
Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data
Gautam Kamath, Xingtu Liu, Huanyu Zhang
Workshop
A Practitioners Guide to Differentially Private Convex Optimization
Ryan McKenna, Hristo Paskov, Kunal Talwar
Workshop
Shuffle Private Stochastic Convex Optimization
Albert Cheu, Matthew Joseph, Jieming Mao, Binghui Peng
Workshop
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization
David Eriksson, Pierce Chuang, Samuel Daulton, Peng Xia, Akshat Shrivastava, Arun Babu, Shicong Zhao, Ahmed A Aly, Ganesh Venkatesh, Maximilian Balandat
Workshop
Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance
Pari Ram, Alexander G Gray, Horst Samulowitz
Workshop
Neural Fixed-Point Acceleration for Convex Optimization
Shobha Venkataraman, Brandon Amos
Workshop
Towards Explaining Hyperparameter Optimization via Partial Dependence Plots
Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
Workshop
Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization
Akihiro Kishimoto, Djallel Bouneffouf, Radu Marinescu, Pari Ram, Ambrish Rawat, Martin Wistuba, paul Palmes, Adi Botea
Workshop
LRTuner: A Learning Rate Tuner for Deep Neural Networks
Nikhil Iyer, Thejas Venkatesh, Nipun Kwatra, Ramachandran Ramjee, Muthian Sivathanu
Workshop
Mutation is all you need
Lennart Schneider, Florian Pfisterer, Martin Binder, Bernd Bischl
Workshop
Replacing the Ex-Def Baseline in AutoML by Naive AutoML
Felix Mohr, Marcel Wever
Workshop
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization
Sergio Izquierdo, Julia Guerrero-Viu, Sven Hauns, Guilherme Miotto, Simon Schrodi, André Biedenkapp, Thomas Elsken, Difan Deng, Marius Lindauer, Frank Hutter
Workshop
Reinforcement Learning for Workflow Recognition in Surgical Videos
Wang Wei, Jingze Zhang, Qi Dou
Workshop
Solving inverse problems with deep neural networks driven by sparse signal decomposition in a physics-based dictionary
Gaetan Rensonnet
Workshop
Flexible Interpretability through Optimizable Counterfactual Explanations for Tree Ensembles
Ana Lucic, Harrie Oosterhuis, Hinda Haned, Maarten de Rijke
Workshop
FERMI: Fair Empirical Risk Minimization Via Exponential Rényi Mutual Information
Andrew Lowy, Rakesh Pavan, Sina Baharlouei, Meisam Razaviyayn, Ahmad Beirami
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
A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs
Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric
Workshop
Learning Adversarial Markov Decision Processes with Delayed Feedback
Tal Lancewicki, Aviv Rosenberg, Yishay Mansour
Workshop
Randomized Least Squares Policy Optimization
Haque Ishfaq, Zhuoran Yang, Andrei Lupu, Viet Nguyen, Lewis Liu, Riashat Islam, Zhaoran Wang, Doina Precup
Workshop
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction
Ming Yin, Yu Bai, Yu-Xiang Wang
Workshop
Nearly Optimal Regret for Learning Adversarial MDPs with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Workshop
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
Workshop
A general sample complexity analysis of vanilla policy gradient
Rui Yuan, Robert Gower, Alessandro Lazaric
Workshop
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Chi Jin, Qinghua Liu, Sobhan Miryoosefi
Workshop
A Boosting Approach to Reinforcement Learning
Nataly Brukhim, Elad Hazan, Karan Singh
Workshop
Refined Policy Improvement Bounds for MDPs
Mark Gluzman
Workshop
Policy Optimization in Adversarial MDPs: Improved Exploration via Dilated Bonuses
Haipeng Luo, Chen-Yu Wei, Chung-Wei Lee
Workshop
Data-driven Experimental Prioritization via Imputation and Submodular Optimization
Jacob Schreiber
Workshop
Opportunities and Challenges in Designing Genomic Sequences
Mengyan Zhang
Workshop
Effective Surrogate Models for Protein Design with Bayesian Optimization
Nate Gruver
Workshop
Multi-target optimization for drug discovery using generative models
Anirudh jain
Workshop
DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning
Xianyuan Zhan, Haoran Xu, Yue Zhang, Xiangyu Zhu, Honglei Yin
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
Coordinate-wise Control Variates for Deep Policy Gradients
Yuanyi Zhong, Yuan Zhou, Jian Peng
Workshop
Learning Space Partitions for Path Planning
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E Gonzalez, Dan Klein, Yuandong Tian
Workshop
Revisiting Design Choices in Offline Model Based Reinforcement Learning
Cong Lu, Philip Ball, Jack Parker-Holder, Michael A Osborne, Stephen Roberts
Workshop
Optimization of high precision manufacturing by Monte Carlo Tree Search
Dorina Weichert, Alexander Kister
Workshop
The Reflective Explorer: Online Meta-Exploration from Offline Data in Visual Tasks with Sparse Rewards
Rafael Rafailov, Varun Kumar, Tianhe (Kevin) Yu, Avi Singh, mariano phielipp, Chelsea Finn
Workshop
Avoiding Overfitting to the Importance Weights in Offline Policy Optimization
Yao Liu, Emma Brunskill
Workshop
ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control
Xingshuai Huang, di wu, Benoit Boulet
Workshop
A Policy Efficient Reduction Approach to Convex Constrained Deep Reinforcement Learning
Tianchi Cai, Wenpeng Zhang, Lihong Gu, Xiaodong Zeng, Jinjie Gu
Workshop
Reinforcement Learning Agent Training with Goals for Real World Tasks
Xuan Zhao
Workshop
Scalable Algorithms for Nonlinear Causal Inference
Gokul Swamy, Sanjiban Choudhury, Drew Bagnell, Steven Wu
Workshop
DFUQ poster 1 -- Conformal Uncertainty Sets for Robust Optimization
Workshop
On The State of Data In Computer Vision: Human Annotations Remain Indispensable for Developing Deep Learning Models.
Zeyad Emam, Sasha Harrison, Felix Lau, Aerin Kim
Workshop
Differentially Private Active Learning with Latent Space Optimization
Samson Cheung, Xiaoqing Zhu, Herb Wildfeuer, Chongruo Wu, Wai-tian Tan
Workshop
Selective Focusing Learning in Conditional GANs
Kyeongbo Kong, Kyunghun Kim, Woo-jin Song, Suk-Ju Kang
Workshop
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee
Tengyu Xu, Yingbin LIANG, Guanghui Lan
Workshop
Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, Woo-jin Song
Workshop
Sparse Bayesian Learning via Stepwise Regression
Sebastian Ament, Carla Gomes
Workshop
Minimax Optimization: The Case of Convex-Submodular
Arman Adibi, Aryan Mokhtari, Hamed Hassani
Workshop
Improved Regret Bounds for Online Submodular Maximization
Omid Sadeghi, Maryam Fazel
Workshop
Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga S, Ganesh Ramakrishnan, Rishabh Lyer
Workshop
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity
Praneeth Vepakomma, Ramesh Raskar
Workshop
ANP-BBO: Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins
Ankush Chakrabarty
Workshop
Attention-Guided Black-box Adversarial Attacks with Large-Scale Multiobjective Evolutionary Optimization
Jie Wang, Zhaoxia Yin, Jing Jiang, Yang Du
Workshop
Towards Safe Reinforcement Learning via Constraining Conditional Value at Risk
Chengyang Ying, Lemon Zhou, Dong Yan, Jun Zhu
Workshop
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang, Eunjung Lee, Wonjong Rhee
Workshop
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
Maura Pintor, Luca Demetrio, Angelo Sotgiu, Giovanni Manca, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli
Workshop
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints
Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio
Workshop
Adversarial EXEmples: Functionality-preserving Optimization of Adversarial Windows Malware
Luca Demetrio, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli, Luca Demetrio
Workshop
On Frank-Wolfe Adversarial Training
Theodoros Tsiligkaridis, Jay Roberts
Workshop
Adversarial Semantic Contour for Object Detection
Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu
Workshop
On Success and Simplicity: A Second Look at Transferable Targeted Attacks
Zhengyu Zhao, Zhuoran Liu, Martha Larson
Workshop
Online and Non Parametric Coresets for Bregman Divergence
Supratim Shit, Rachit Chhaya, Anirban Dasgupta, Jayesh Choudhari
Workshop
GoldiProx Selection: Faster training by learning what is learnable, not yet learned, and worth learning
Sören Mindermann, Muhammed Razzak, Adrien Morisot, Aidan Gomez, Sebastian Farquhar, Jan Brauner, Yarin Gal
Workshop
CounterNet: End-to-End Training of Counterfactual Aware Predictions
Hangzhi Guo, Thanh Nguyen, Amulya Yadav
Workshop
Amortized Sequential Counterfactual Explanations for Black-box Models
Sahil Verma, Keegan Hines, John Dickerson
Workshop
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen, Nikita Agarwal, Jakob Zeitler, Afsaneh Mastouri, Bernhard Schölkopf
Workshop
Generalization Error and Overparameterization While Learning over Networks
Martin Hellkvist, Ayca Ozcelikkale
Workshop
How does Over-Parametrization Lead to Acceleration for Learning a Single Teacher Neuron with Quadratic Activation?
Jun-Kun Wang, Jake Abernethy
Workshop
Label Noise SGD Provably Prefers Flat Global Minimizers
Alex Damian, Tengyu Ma, Jason Lee
Workshop
On Low Rank Training of Deep Neural Networks
Sid Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan Gomez
Workshop
On the Sparsity of Deep Neural Networks in the Overparameterized Regime: An Empirical Study
Rahul Parhi, Jack Wolf, Robert Nowak
Workshop
Epoch-Wise Double Descent: A Theory of Multi-scale Feature Learning Dynamics
Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
Workshop
A Data Subset Selection Framework for Efficient Hyper-Parameter Tuning and Automatic Machine Learning
Savan Amitbhai Visalpara, Krishnateja Killamsetty, Rishabh Lyer
Workshop
Multi-objective diversification via Submodular Counterfactual Scoring for Track Sequencing on Spotify
Rishabh Mehrotra
Workshop
Practical posterior Laplace approximation with optimization-driven second moment estimation
Workshop
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
Terrance Liu, Giuseppe Vietri, Steven Wu
Workshop
Benchmarking Differential Privacy and Federated Learning for BERT Models
Priyam Basu, Rakshit Naidu, Zumrut Muftuoglu, Sahib Singh, FatemehSadat Mireshghallah
Workshop
Unsupervised Information Obfuscation for Split Inference of Neural Networks
Mohammad Samragh, Hossein Hosseini, Aleksei Triastcyn, Kambiz Azarian, Joseph B Soriaga, Farinaz Koushanfar
Workshop
Within-layer Diversity Reduces Generalization Gap
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Moncef Gabbouj
Workshop
Out-of-Distribution Robustness in Deep Learning Compression
Eric Lei, Hamed Hassani
Workshop
MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization
Workshop
BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning
Workshop
Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization over Time-Varying Networks
Workshop
Private Multi-Task Learning: Formulation and Applications to Federated Learning
Shengyuan Hu, Steven Wu, Virginia Smith
Workshop
Non-Euclidean Differentially Private Stochastic Convex Optimization
Raef Bassily, Cristobal Guzman, Anupama Nandi
Workshop
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization
Pranav Subramani, Nicholas Vadivelu, Gautam Kamath
Workshop
Adapting to function difficulty and growth conditions in private optimization
Hilal Asi, Daniel A Levy, John Duchi
Workshop
Differentially Private Bayesian Neural Network
Woody Bu, Qiyiwen Zhang, Kan Chen, Qi Long
Workshop
Iterative Methods for Private Synthetic Data: Unifying Framework and New Methods
Terrance Liu, Giuseppe Vietri, Steven Wu
Workshop
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection
Shubhankar Mohapatra, Shubhankar Mohapatra, Sajin Sasy, Gautam Kamath, Xi He, Om Thakkar