391 Results

Expo Talk Panel
Sat 21:45 How We Leverage Machine Learning and AI to Develop Life-Changing Medicines - A Case Study with COVID-19.
Mary Ellen Perry
Expo Talk Panel
Sun 6:30 Federated Reinforcement Learning for Financial Portfolio Optimization Using the IBM Federated Learning (IFL) Platform
Mary Ellen Perry
Tutorial
Mon 1:00 Machine Learning with Signal Processing
Arno Solin
AffinityWorkshop
Mon 2:25 Breakout Session 2.2 Recent applications of Bayesian optimization - CANCELED
Test Of Time
Mon 4:00 Test of Time: Gaussian Process Optimization in the Bandit Settings: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham Kakade, Matthias W Seeger
Tutorial
Mon 5:00 Parameter-free Online Optimization
Francesco Orabona, Ashok Cutkosky
Tutorial
Mon 8:00 Bayesian Deep Learning and a Probabilistic Perspective of Model Construction
Andrew Wilson
Tutorial
Mon 8:00 Submodular Optimization: From Discrete to Continuous and Back
Hamed Hassani, Amin Karbasi
AffinityWorkshop
Mon 9:45 Breakout Session 3.8: Optimization Challenges of Generative Adversarial Networks
Poster
Tue 7:00 Customizing ML Predictions for Online Algorithms
Keerti Anand, Rong Ge, Debmalya Panigrahi
Poster
Tue 7:00 Scalable Nearest Neighbor Search for Optimal Transport
Arturs Backurs, Yihe Dong, Piotr Indyk, Ilya Razenshteyn, Tal Wagner
Poster
Tue 7:00 Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising
Xiaotian Hao, Zhaoqing Peng, Yi Ma, Guan Wang, Junqi Jin, Jianye Hao, Shan Chen, Rongquan Bai, Mingzhou Xie, Miao Xu, Zhenzhe Zheng, Chuan Yu, HAN LI, Jian Xu, Kun Gai
Poster
Tue 7:00 Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai, H. Vincent Poor, Yuxin Chen
Poster
Tue 7:00 Fast and Private Submodular and $k$-Submodular Functions Maximization with Matroid Constraints
Akbar Rafiey, Yuichi Yoshida
Poster
Tue 7:00 Manifold Identification for Ultimately Communication-Efficient Distributed Optimization
Yu-Sheng Li, Wei-Lin Chiang, Ching-pei Lee
Poster
Tue 7:00 Stochastic Optimization for Non-convex Inf-Projection Problems
Yan Yan, Yi Xu, Lijun Zhang, Wang Xiaoyu, Tianbao Yang
Poster
Tue 7:00 Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study
Tanner Fiez, Benjamin Chasnov, Lillian Ratliff
Poster
Tue 7:00 Accelerated Stochastic Gradient-free and Projection-free Methods
Feihu Huang, Lue Tao, Songcan Chen
Poster
Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO, Hansi Yang, Bo Han, Gang Niu, James Kwok
Poster
Tue 7:00 On Second-Order Group Influence Functions for Black-Box Predictions
Samyadeep Basu, Xuchen You, Soheil Feizi
Poster
Tue 7:00 Streaming k-Submodular Maximization under Noise subject to Size Constraint
Lan N. Nguyen, My T. Thai
Poster
Tue 7:00 On the Noisy Gradient Descent that Generalizes as SGD
Jingfeng Wu, Wenqing Hu, Haoyi Xiong, Jun Huan, Vladimir Braverman, Zhanxing Zhu
Poster
Tue 7:00 MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time
XICHUAN ZHOU, YiCong Peng, Chunqiao Long, Fengbo Ren, Cong Shi
Poster
Tue 7:00 Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Martin Mladenov, Elliot Creager, Omer Ben-Porat, Kevin Swersky, Richard Zemel, Craig Boutilier
Poster
Tue 7:00 Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning
Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire, Carla Gomes
Poster
Tue 7:00 What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?
Chi Jin, Praneeth Netrapalli, Michael Jordan
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong, Bo Zeng
Poster
Tue 7:00 On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 7:00 Individual Fairness for k-Clustering
Sepideh Mahabadi, Ali Vakilian
Poster
Tue 7:00 Taylor Expansion Policy Optimization
Yunhao Tang, Michal Valko, Remi Munos
Poster
Tue 7:00 Layered Sampling for Robust Optimization Problems
Hu Ding, Zixiu Wang
Poster
Tue 7:00 Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions
Kaito Fujii
Poster
Tue 7:00 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
shuai zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
Poster
Tue 7:00 Streaming Submodular Maximization under a k-Set System Constraint
Ran Haba, Ehsan Kazemi, Moran Feldman, Amin Karbasi
Poster
Tue 7:00 Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar
Poster
Tue 7:00 FetchSGD: Communication-Efficient Federated Learning with Sketching
Daniel Rothchild, Ashwinee Panda, Enayat Ullah, Nikita Ivkin, Ion Stoica, Vladimir Braverman, Joseph Gonzalez, Raman Arora
Poster
Tue 7:00 Quadratically Regularized Subgradient Methods for Weakly Convex Optimization with Weakly Convex Constraints
Runchao Ma, Qihang Lin, Tianbao Yang
Poster
Tue 7:00 Zeno++: Robust Fully Asynchronous SGD
Cong Xie, Sanmi Koyejo, Indranil Gupta
Poster
Tue 7:00 Semismooth Newton Algorithm for Efficient Projections onto $\ell_{1, \infty}$-norm Ball
Dejun Chu, Changshui Zhang, Shiliang Sun, Qing Tao
Poster
Tue 7:00 Differentiating through the Fréchet Mean
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Sernam Lim Lim, Christopher De Sa
Poster
Tue 7:00 Towards Understanding the Dynamics of the First-Order Adversaries
Zhun Deng, Hangfeng He, Jiaoyang Huang, Weijie Su
Poster
Tue 7:00 Two Routes to Scalable Credit Assignment without Weight Symmetry
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena, Surya Ganguli, Jon Bloom, Daniel Yamins
Poster
Tue 7:00 Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O'Reilly
Poster
Tue 7:00 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization
Richard Zhang, Daniel Golovin
Poster
Tue 7:00 Self-Concordant Analysis of Frank-Wolfe Algorithms
Pavel Dvurechenskii, Petr Ostroukhov, Kamil Safin, Shimrit Shtern, Mathias Staudigl
Poster
Tue 7:00 Provably Efficient Exploration in Policy Optimization
Qi Cai, Zhuoran Yang, Chi Jin, Zhaoran Wang
Poster
Tue 7:00 Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L.A., Krishna Jagannathan, Ravi Kolla
Poster
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiru Bhattacharyya, Ravindran Kannan
Poster
Tue 8:00 Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
Kunal Menda, Jean de Becdelievre, Jayesh Gupta, Ilan Kroo, Mykel Kochenderfer, Zachary Manchester
Poster
Tue 8:00 FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
Aman Sinha, Matthew O'Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake
Poster
Tue 8:00 Batch Reinforcement Learning with Hyperparameter Gradients
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
Poster
Tue 8:00 Is Local SGD Better than Minibatch SGD?
Blake Woodworth, Kumar Kshitij Patel, Sebastian Stich, Zhen Dai, Brian Bullins, Brendan McMahan, Ohad Shamir, Nati Srebro
Poster
Tue 8:00 Finite-Time Convergence in Continuous-Time Optimization
Orlando Romero, mouhacine Benosman
Poster
Tue 8:00 Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization
Rie Johnson, Tong Zhang
Poster
Tue 8:00 The Tree Ensemble Layer: Differentiability meets Conditional Computation
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
Poster
Tue 8:00 Closing the convergence gap of SGD without replacement
Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos
Poster
Tue 8:00 Stronger and Faster Wasserstein Adversarial Attacks
Kaiwen Wu, Allen Wang, Yaoliang Yu
Poster
Tue 8:00 Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate
Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 8:00 GradientDICE: Rethinking Generalized Offline Estimation of Stationary Values
Shangtong Zhang, Bo Liu, Shimon Whiteson
Poster
Tue 8:00 Invariant Risk Minimization Games
Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar
Poster
Tue 8:00 Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
Yun Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Poster
Tue 8:00 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards
Umer Siddique, Paul Weng, Matthieu Zimmer
Poster
Tue 8:00 Angular Visual Hardness
Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Anima Anandkumar
Poster
Tue 8:00 On the Unreasonable Effectiveness of the Greedy Algorithm: Greedy Adapts to Sharpness
Sebastian Pokutta, Mohit Singh, Alfredo Torrico
Poster
Tue 8:00 Distributed Online Optimization over a Heterogeneous Network
Nima Eshraghi, Ben Liang
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu
Poster
Tue 9:00 Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
Somdeb Majumdar, Shauharda Khadka, Santiago Miret, Stephen Mcaleer, Kagan Tumer
Poster
Tue 9:00 Nearly Linear Row Sampling Algorithm for Quantile Regression
Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang
Poster
Tue 9:00 A Chance-Constrained Generative Framework for Sequence Optimization
Xianggen Liu, Qiang Liu, Sen Song , Jian Peng
Poster
Tue 9:00 Structured Policy Iteration for Linear Quadratic Regulator
Youngsuk Park, Ryan Rossi, Zheng Wen, Gang Wu, Handong Zhao
Poster
Tue 9:00 Streaming Coresets for Symmetric Tensor Factorization
Supratim Shit, Rachit Chhaya, Jayesh Choudhari, Anirban Dasgupta
Poster
Tue 9:00 Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu, Vladimir Braverman, Lin Yang
Poster
Tue 9:00 Robustness to Spurious Correlations via Human Annotations
Megha Srivastava, Tatsunori Hashimoto, Percy Liang
Poster
Tue 9:00 Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Poster
Tue 9:00 Variance Reduction in Stochastic Particle-Optimization Sampling
Jianyi Zhang, Yang Zhao, Changyou Chen
Poster
Tue 9:00 Fast OSCAR and OWL Regression via Safe Screening Rules
Runxue Bao, Bin Gu, Heng Huang
Poster
Tue 10:00 Differentiable Likelihoods for Fast Inversion of 'Likelihood-Free' Dynamical Systems
Hans Kersting, Nicholas Krämer, Martin Schiegg, Christian Daniel, Michael Schober, Philipp Hennig
Poster
Tue 10:00 Training Deep Energy-Based Models with f-Divergence Minimization
Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon
Poster
Tue 10:00 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank Jakkam Reddi, Sebastian Stich, Ananda Theertha Suresh
Poster
Tue 10:00 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Misha Khodak, Sanjeev Arora
Poster
Tue 10:00 Fully Parallel Hyperparameter Search: Reshaped Space-Filling
Marie-Liesse Cauwet, Camille Couprie, Julien Dehos, Pauline Luc, Jeremy Rapin, Morgane Riviere, Fabien Teytaud, Olivier Teytaud, Nicolas Usunier
Poster
Tue 10:00 Incremental Sampling Without Replacement for Sequence Models
Kensen Shi, David Bieber, Charles Sutton
Poster
Tue 10:00 Deep Isometric Learning for Visual Recognition
Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik
Poster
Tue 10:00 Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis
Shuang Qiu, Xiaohan Wei, Zhuoran Yang
Poster
Tue 10:00 Global Concavity and Optimization in a Class of Dynamic Discrete Choice Models
Yiding Feng, Ekaterina Khmelnitskaya, Denis Nekipelov
Poster
Tue 10:00 A simpler approach to accelerated optimization: iterative averaging meets optimism
Pooria Joulani, Anant Raj, András György, Csaba Szepesvari
Poster
Tue 10:00 Responsive Safety in Reinforcement Learning by PID Lagrangian Methods
Adam Stooke, Joshua Achiam, Pieter Abbeel
Poster
Tue 10:00 Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning
Amin Rakhsha, Goran Radanovic, Rati Devidze, Jerry Zhu, Adish Singla
Poster
Tue 11:00 Smaller, more accurate regression forests using tree alternating optimization
Arman Zharmagambetov, Miguel Carreira-Perpinan
Poster
Tue 11:00 Near-linear time Gaussian process optimization with adaptive batching and resparsification
Daniele Calandriello, Luigi Carratino, Alessandro Lazaric, Michal Valko, Lorenzo Rosasco
Poster
Tue 11:00 Online metric algorithms with untrusted predictions
Antonios Antoniadis, Christian Coester, Marek Elias, Adam Polak, Bertrand Simon
Poster
Tue 11:00 A Swiss Army Knife for Minimax Optimal Transport
Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
Poster
Tue 11:00 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
Poster
Tue 11:00 Information-Theoretic Local Minima Characterization and Regularization
Zhiwei Jia, Hao Su
Poster
Tue 11:00 Optimization and Analysis of the pAp@k Metric for Recommender Systems
Gaurush Hiranandani, Warut Vijitbenjaronk, Sanmi Koyejo, Prateek Jain
Poster
Tue 12:00 IPBoost – Non-Convex Boosting via Integer Programming
Marc Pfetsch, Sebastian Pokutta
Poster
Tue 12:00 A distributional view on multi-objective policy optimization
Abbas Abdolmaleki, Sandy Huang, Leonard Hasenclever, Michael Neunert, Francis Song, Martina Zambelli, Murilo Martins, Nicolas Heess, Raia Hadsell, Martin Riedmiller
Poster
Tue 12:00 Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization
GEOFFREY Negiar, Gideon Dresdner, Alicia Yi-Ting Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
Poster
Tue 12:00 SimGANs: Simulator-Based Generative Adversarial Networks for ECG Synthesis to Improve Deep ECG Classification
Tomer Golany, Kira Radinsky, Daniel Freedman
Poster
Tue 12:00 Ready Policy One: World Building Through Active Learning
Philip Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts
Poster
Tue 13:00 StochasticRank: Global Optimization of Scale-Free Discrete Functions
Aleksei Ustimenko, Liudmila Prokhorenkova
Poster
Tue 13:00 Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, Michael Carbin
Poster
Tue 13:00 Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses
Pierre Laforgue, Alex Lambert, Luc Brogat-Motte, Florence d'Alche-Buc
Poster
Tue 13:00 Online Convex Optimization in the Random Order Model
Dan Garber, Gal Korcia, Kfir Levy
Poster
Tue 13:00 Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization
Hien Le, Nicolas Gillis, Panagiotis Patrinos
Poster
Tue 13:00 Optimal Randomized First-Order Methods for Least-Squares Problems
Jonathan Lacotte, Mert Pilanci
Poster
Tue 13:00 Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise
Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gurbuzbalaban
Poster
Tue 13:00 Inexact Tensor Methods with Dynamic Accuracies
Nikita Doikov, Yurii Nesterov
Poster
Tue 13:00 Implicit differentiation of Lasso-type models for hyperparameter optimization
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon
Poster
Tue 14:00 On the Iteration Complexity of Hypergradient Computation
Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo
Poster
Tue 14:00 Optimal Estimator for Unlabeled Linear Regression
Hang Zhang, Ping Li
Poster
Tue 14:00 Extreme Multi-label Classification from Aggregated Labels
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit Dhillon
Poster
Tue 14:00 Debiased Sinkhorn barycenters
Hicham Janati, Marco Cuturi, Alexandre Gramfort
Poster
Tue 14:00 Compressive sensing with un-trained neural networks: Gradient descent finds a smooth approximation
Reinhard Heckel, Mahdi Soltanolkotabi
Poster
Tue 14:00 Knowing The What But Not The Where in Bayesian Optimization
Vu Nguyen, Michael A Osborne
Poster
Tue 14:00 Training Neural Networks for and by Interpolation
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Poster
Tue 14:00 Fast Differentiable Sorting and Ranking
Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
Poster
Tue 15:00 When deep denoising meets iterative phase retrieval
Yaotian Wang, Xiaohang Sun, Jason Fleischer
Poster
Tue 15:00 Thompson Sampling Algorithms for Mean-Variance Bandits
Qiuyu Zhu, Vincent Tan
Poster
Tue 15:00 Invertible generative models for inverse problems: mitigating representation error and dataset bias
Muhammad Asim, Max Daniels, Oscar Leong, Ali Ahmed, Paul Hand
Poster
Tue 18:00 Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
Poster
Tue 18:00 Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space
Keizo Kato, Jing Zhou, Tomotake Sasaki, Akira Nakagawa
Poster
Tue 18:00 Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
Pan Zhou, Xiao-Tong Yuan
Poster
Tue 18:00 Learning to Learn Kernels with Variational Random Features
Xiantong Zhen, Haoliang Sun, Yingjun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek
Poster
Tue 19:00 DessiLBI: Exploring Structural Sparsity of Deep Networks via Differential Inclusion Paths
Yanwei Fu, Chen Liu, Donghao Li, Xinwei Sun, Jinshan ZENG, Yuan Yao
Poster
Wed 5:00 Optimal Bounds between f-Divergences and Integral Probability Metrics
Rohit Agrawal, Thibaut Horel
Poster
Wed 5:00 Operation-Aware Soft Channel Pruning using Differentiable Masks
Minsoo Kang, Bohyung Han
Poster
Wed 5:00 Can Stochastic Zeroth-Order Frank-Wolfe Method Converge Faster for Non-Convex Problems?
Hongchang Gao, Heng Huang
Poster
Wed 5:00 Population-Based Black-Box Optimization for Biological Sequence Design
Christof Angermueller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D. Sculley
Poster
Wed 5:00 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba
Poster
Wed 5:00 Second-Order Provable Defenses against Adversarial Attacks
Sahil Singla, Soheil Feizi
Poster
Wed 5:00 Learning What to Defer for Maximum Independent Sets
Sungsoo Ahn, Younggyo Seo, Jinwoo Shin
Poster
Wed 5:00 Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations
Stephen Keeley, David Zoltowski, Yiyi Yu, Spencer Smith, Jonathan Pillow
Poster
Wed 5:00 Robust Bayesian Classification Using An Optimistic Score Ratio
Viet Anh Nguyen, Nian Si, Jose Blanchet
Poster
Wed 5:00 Complexity of Finding Stationary Points of Nonconvex Nonsmooth Functions
Jingzhao Zhang, Hongzhou Lin, Stefanie Jegelka, Suvrit Sra, Ali Jadbabaie
Poster
Wed 5:00 An Accelerated DFO Algorithm for Finite-sum Convex Functions
Yuwen Chen, Antonio Orvieto, Aurelien Lucchi
Poster
Wed 5:00 Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
Vladimir Braverman, Robert Krauthgamer, Aditya Krishnan, Roi Sinoff
Poster
Wed 5:00 Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
Jiaoyang Huang, Horng-Tzer Yau
Poster
Wed 5:00 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
Bo Han, Gang Niu, Xingrui Yu, QUANMING YAO, Miao Xu, Ivor Tsang, Masashi Sugiyama
Poster
Wed 5:00 Eliminating the Invariance on the Loss Landscape of Linear Autoencoders
Reza Oftadeh, Jiayi Shen, Zhangyang Wang, Dylan Shell
Poster
Wed 5:00 Moniqua: Modulo Quantized Communication in Decentralized SGD
Yucheng Lu, Christopher De Sa
Poster
Wed 5:00 Optimal approximation for unconstrained non-submodular minimization
Marwa El Halabi, Stefanie Jegelka
Poster
Wed 5:00 Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
Jie Xu, Yunsheng Tian, Pingchuan Ma, Daniela Rus, Shinjiro Sueda, Wojciech Matusik
Poster
Wed 5:00 Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript
Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui
Poster
Wed 5:00 Message Passing Least Squares Framework and its Application to Rotation Synchronization
Yunpeng Shi, Gilad Lerman
Poster
Wed 5:00 Efficient Intervention Design for Causal Discovery with Latents
Raghavendra Addanki, Shiva Kasiviswanathan, Andrew McGregor, Cameron Musco
Poster
Wed 5:00 Learning Quadratic Games on Networks
Yan Leng, Xiaowen Dong, Junfeng Wu, Alex `Sandy' Pentland
Poster
Wed 5:00 One Size Fits All: Can We Train One Denoiser for All Noise Levels?
Abhiram Gnanasambandam, Stanley Chan
Poster
Wed 5:00 Reinforcement Learning for Integer Programming: Learning to Cut
Yunhao Tang, Shipra Agrawal, Yuri Faenza
Poster
Wed 5:00 Robust and Stable Black Box Explanations
Himabindu Lakkaraju, Nino Arsov, Osbert Bastani
Poster
Wed 5:00 The Differentiable Cross-Entropy Method
Brandon Amos, Denis Yarats
Poster
Wed 5:00 On the Convergence of Nesterov's Accelerated Gradient Method in Stochastic Settings
Mido Assran, Mike Rabbat
Poster
Wed 8:00 Spectral Graph Matching and Regularized Quadratic Relaxations: Algorithm and Theory
Zhou Fan, Cheng Mao, Yihong Wu, Jiaming Xu
Poster
Wed 8:00 Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta
Poster
Wed 8:00 Online mirror descent and dual averaging: keeping pace in the dynamic case
Huang Fang, Nick Harvey, Victor Sanches Portella, Michael Friedlander
Poster
Wed 8:00 Choice Set Optimization Under Discrete Choice Models of Group Decisions
Kiran Tomlinson, Austin Benson
Poster
Wed 8:00 Budgeted Online Influence Maximization
Pierre Perrault, Jen A Healey, Zheng Wen, Michal Valko
Poster
Wed 8:00 Self-Modulating Nonparametric Event-Tensor Factorization
Zheng Wang, Xinqi Chu, Shandian Zhe
Poster
Wed 8:00 Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Krzysztof Choromanski, Anna Choromanska, Michael Jordan
Poster
Wed 8:00 Stochastic Gradient and Langevin Processes
Xiang Cheng, Dong Yin, Peter Bartlett, Michael Jordan
Poster
Wed 8:00 Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
Yunwen Lei, Yiming Ying
Poster
Wed 8:00 Optimal transport mapping via input convex neural networks
Ashok Makkuva, Amir Taghvaei, Sewoong Oh, Jason Lee
Poster
Wed 8:00 Decoupled Greedy Learning of CNNs
Eugene Belilovsky, Michael Eickenberg, Edouard Oyallon
Poster
Wed 8:00 The Non-IID Data Quagmire of Decentralized Machine Learning
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phil Gibbons
Poster
Wed 8:00 Safe screening rules for L0-regression from Perspective Relaxations
Alper Atamturk, Andres Gomez
Poster
Wed 8:00 Private Outsourced Bayesian Optimization
Dmitrii Kharkovskii, Zhongxiang Dai, Bryan Kian Hsiang Low
Poster
Wed 8:00 Adversarial Mutual Information for Text Generation
Boyuan Pan, Yazheng Yang, Kaizhao Liang, Bhavya Kailkhura, Zhongming Jin, Xian-Sheng Hua, Deng Cai, Bo Li
Poster
Wed 8:00 Communication-Efficient Distributed PCA by Riemannian Optimization
Long-Kai Huang, Sinno Jialin Pan
Poster
Wed 8:00 On Coresets for Regularized Regression
Rachit Chhaya, Supratim Shit, Anirban Dasgupta
Poster
Wed 9:00 Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search
Binghong Chen, Chengtao Li, Hanjun Dai, Le Song
Poster
Wed 9:00 Optimization Theory for ReLU Neural Networks Trained with Normalization Layers
Yonatan Dukler, Quanquan Gu, Guido Montufar
Poster
Wed 9:00 A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
Yiping Lu, Chao Ma, Yulong Lu, Jianfeng Lu, Lexing Ying
Poster
Wed 9:00 Accountable Off-Policy Evaluation With Kernel Bellman Statistics
Yihao Feng, Tongzheng Ren, Ziyang Tang, Qiang Liu
Poster
Wed 9:00 Dual Mirror Descent for Online Allocation Problems
Santiago Balseiro, Haihao Lu, Vahab Mirrokni
Poster
Wed 10:00 Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
Poster
Wed 10:00 Learning to Simulate and Design for Structural Engineering
Kai-Hung Chang, Chin-Yi Cheng
Poster
Wed 10:00 AdaScale SGD: A User-Friendly Algorithm for Distributed Training
Tyler Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin
Poster
Wed 10:00 Hierarchical Verification for Adversarial Robustness
Cong Han Lim, Raquel Urtasun, Ersin Yumer
Poster
Wed 10:00 How to Solve Fair k-Center in Massive Data Models
Ashish Chiplunkar, Sagar Kale, Sivaramakrishnan Natarajan Ramamoorthy
Poster
Wed 10:00 Efficiently Solving MDPs with Stochastic Mirror Descent
Yujia Jin, Aaron Sidford
Poster
Wed 10:00 Provable Representation Learning for Imitation Learning via Bi-level Optimization
Sanjeev Arora, Simon Du, Sham Kakade, Yuping Luo, Nikunj Saunshi
Poster
Wed 10:00 Continuous-time Lower Bounds for Gradient-based Algorithms
Michael Muehlebach, Michael Jordan
Poster
Wed 10:00 Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks
Mert Pilanci, Tolga Ergen
Poster
Wed 10:00 Quantized Decentralized Stochastic Learning over Directed Graphs
Hossein Taheri, Aryan Mokhtari, Hamed Hassani, Ramtin Pedarsani
Poster
Wed 11:00 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulié
Poster
Wed 11:00 Adaptive Gradient Descent without Descent
Yura Malitsky, Konstantin Mishchenko
Poster
Wed 11:00 PackIt: A Virtual Environment for Geometric Planning
Ankit Goyal, Jia Deng
Poster
Wed 11:00 Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach, Gilad Yehudai, Shai Shalev-Schwartz, Ohad Shamir
Poster
Wed 11:00 From Local SGD to Local Fixed-Point Methods for Federated Learning
Grigory Malinovsky, Dmitry Kovalev, Elnur Gasanov, Laurent CONDAT, Peter Richtarik
Poster
Wed 12:00 Too Relaxed to Be Fair
Michael Lohaus, Michaël Perrot, Ulrike von Luxburg
Poster
Wed 12:00 Adversarial Nonnegative Matrix Factorization
lei luo, yanfu Zhang, Heng Huang
Poster
Wed 12:00 Curvature-corrected learning dynamics in deep neural networks
Dongsung Huh
Poster
Wed 12:00 Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition
Alex Gittens, Kareem Aggour, Bülent Yener
Poster
Wed 12:00 On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion
Poster
Wed 12:00 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation
Marc Abeille, Alessandro Lazaric
Poster
Wed 12:00 Unique Properties of Flat Minima in Deep Networks
Rotem Mulayoff, Tomer Michaeli
Poster
Wed 12:00 A new regret analysis for Adam-type algorithms
Ahmet Alacaoglu, Yura Malitsky, Panayotis Mertikopoulos, Volkan Cevher
Poster
Wed 12:00 Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
Alexey Drutsa
Poster
Wed 12:00 Training Linear Neural Networks: Non-Local Convergence and Complexity Results
Armin Eftekhari
Poster
Wed 12:00 Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
Zhize Li, Dmitry Kovalev, Xun Qian, Peter Richtarik
Poster
Wed 12:00 Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation
Konstantinos Pitas
Poster
Wed 13:00 Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
Vien Van Mai, Mikael Johansson
Poster
Wed 13:00 A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian Stich
Poster
Wed 13:00 Up or Down? Adaptive Rounding for Post-Training Quantization
Markus Nagel, Rana Ali Amjad, Mart van Baalen, Christos Louizos, Tijmen Blankevoort
Poster
Wed 13:00 Involutive MCMC: a Unifying Framework
Kirill Neklyudov, Max Welling, Evgenii Egorov, Dmitry Vetrov
Poster
Wed 13:00 On the Generalization Benefit of Noise in Stochastic Gradient Descent
Samuel Smith, Erich Elsen, Soham De
Poster
Wed 13:00 Super-efficiency of automatic differentiation for functions defined as a minimum
Pierre Ablin, Gabriel Peyré, Thomas Moreau
Poster
Wed 13:00 A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu
Poster
Wed 13:00 Estimating the Error of Randomized Newton Methods: A Bootstrap Approach
Miles Lopes, Jessie X.T. Chen
Poster
Wed 13:00 Boosting Frank-Wolfe by Chasing Gradients
Cyrille W. Combettes, Sebastian Pokutta
Poster
Wed 13:00 Interference and Generalization in Temporal Difference Learning
Emmanuel Bengio, Joelle Pineau, Doina Precup
Poster
Wed 14:00 Lifted Disjoint Paths with Application in Multiple Object Tracking
Andrea Hornakova, Roberto Henschel, Bodo Rosenhahn, Paul Swoboda
Poster
Wed 14:00 Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
Filip Hanzely, Dmitry Kovalev, Peter Richtarik
Poster
Wed 14:00 Explicit Gradient Learning for Black-Box Optimization
Elad Sarafian, Mor Sinay, yoram louzoun, Noa Agmon, Sarit Kraus
Poster
Wed 15:00 LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction
Vlad Niculae, Andre Filipe Torres Martins
Poster
Wed 15:00 DINO: Distributed Newton-Type Optimization Method
Rixon Crane, Fred Roosta
Poster
Wed 15:00 Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
Chengcheng Wan, Henry (Hank) Hoffmann, Shan Lu, Michael Maire
Poster
Wed 16:00 Online Dense Subgraph Discovery via Blurred-Graph Feedback
Yuko Kuroki, Atsushi Miyauchi, Junya Honda, Masashi Sugiyama
Poster
Wed 16:00 Bidirectional Model-based Policy Optimization
Hang Lai, Jian Shen, Weinan Zhang, Yong Yu
Poster
Wed 16:00 Optimization from Structured Samples for Coverage Functions
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
Poster
Thu 6:00 Performative Prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, University of California Moritz Hardt
Poster
Thu 6:00 Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space
Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang
Poster
Thu 6:00 Input-Sparsity Low Rank Approximation in Schatten Norm
Yi Li, David Woodruff
Poster
Thu 6:00 Rigging the Lottery: Making All Tickets Winners
Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
Poster
Thu 6:00 On the Expressivity of Neural Networks for Deep Reinforcement Learning
Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma
Poster
Thu 6:00 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
Kaiyi Ji, Zhe Wang, Bowen Weng, Yi Zhou, Wei Zhang, Yingbin LIANG
Poster
Thu 6:00 p-Norm Flow Diffusion for Local Graph Clustering
Kimon Fountoulakis, Di Wang, Shenghao Yang
Poster
Thu 6:00 Upper bounds for Model-Free Row-Sparse Principal Component Analysis
Guanyi Wang, Santanu Dey
Poster
Thu 6:00 Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization
Deb Mahapatra, Vaibhav Rajan
Poster
Thu 6:00 Scalable Differentiable Physics for Learning and Control
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Poster
Thu 6:00 GraphOpt: Learning Optimization Models of Graph Formation
Rakshit Trivedi, Jiachen Yang, Hongyuan Zha
Poster
Thu 6:00 Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems
Guangzeng Xie, Luo Luo, yijiang lian, Zhihua Zhang
Poster
Thu 6:00 Optimizing Dynamic Structures with Bayesian Generative Search
Minh Hoang, Carleton Kingsford
Poster
Thu 6:00 Amortized Finite Element Analysis for Fast PDE-Constrained Optimization
Tianju Xue, Alex Beatson, Sigrid Adriaenssens , Ryan P. Adams
Poster
Thu 6:00 Linear Lower Bounds and Conditioning of Differentiable Games
Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas
Poster
Thu 6:00 Stochastic Flows and Geometric Optimization on the Orthogonal Group
Krzysztof Choromanski, David Cheikhi, Jared Quincy Davis, Valerii Likhosherstov, Achille Nazaret, Achraf Bahamou, Xingyou Song, Mrugank Akarte, Jack Parker-Holder, Jacob Bergquist, Yuan Gao, Aldo Pacchiano, Tamas Sarlos, Adrian Weller, Vikas Sindhwani
Poster
Thu 6:00 Multi-Agent Routing Value Iteration Network
Quinlan Sykora, Mengye Ren, Raquel Urtasun
Poster
Thu 6:00 Concise Explanations of Neural Networks using Adversarial Training
PRASAD Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha
Poster
Thu 6:00 Do GANs always have Nash equilibria?
Farzan Farnia, Asuman Ozdaglar
Poster
Thu 6:00 Transparency Promotion with Model-Agnostic Linear Competitors
Hassan Rafique, Tong Wang, Qihang Lin, Arshia Singhani
Poster
Thu 6:00 BINOCULARS for efficient, nonmyopic sequential experimental design
Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett
Poster
Thu 6:00 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Quoc Tran-Dinh, Nate H Pham, Lam Nguyen
Poster
Thu 6:00 FACT: A Diagnostic for Group Fairness Trade-offs
Joon Kim, Jiahao Chen, Ameet Talwalkar
Poster
Thu 6:00 Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle
Shaocong Ma, Yi Zhou
Poster
Thu 6:00 Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
Sudeep Salgia, Qing Zhao, Sattar Vakili
Poster
Thu 6:00 Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag
Poster
Thu 6:00 Born-again Tree Ensembles
Thibaut Vidal, Maximilian Schiffer
Poster
Thu 6:00 Improving Transformer Optimization Through Better Initialization
Xiao Shi Huang, Felipe Perez, Jimmy Ba, Maksims Volkovs
Poster
Thu 6:00 Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima
Poster
Thu 6:00 Interpreting Robust Optimization via Adversarial Influence Functions
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Poster
Thu 6:00 A Generic First-Order Algorithmic Framework for Bi-Level Programming Beyond Lower-Level Singleton
Risheng Liu, Pan Mu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
Poster
Thu 6:00 Learning Selection Strategies in Buchberger’s Algorithm
Dylan Peifer, Michael Stillman, Daniel Halpern-Leistner
Poster
Thu 6:00 Refined bounds for algorithm configuration: The knife-edge of dual class approximability
Nina Balcan, Tuomas Sandholm, Ellen Vitercik
Poster
Thu 6:00 Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan
Poster
Thu 6:00 Acceleration through spectral density estimation
Fabian Pedregosa, Damien Scieur
Poster
Thu 6:00 Towards Accurate Post-training Network Quantization via Bit-Split and Stitching
Peisong Wang, Qiang Chen, Xiangyu He, Jian Cheng
Poster
Thu 6:00 Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
Kyriakos Axiotis, Maxim Sviridenko
Poster
Thu 6:00 Almost Tune-Free Variance Reduction
Bingcong Li, Lingda Wang, Georgios B. Giannakis
Poster
Thu 6:00 On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
Darren Lin, Chi Jin, Michael Jordan
Poster
Thu 6:00 Universal Asymptotic Optimality of Polyak Momentum
Damien Scieur, Fabian Pedregosa
Poster
Thu 6:00 New Oracle-Efficient Algorithms for Private Synthetic Data Release
Giuseppe Vietri, Grace Tian, Mark Bun, Thomas Steinke, Steven Wu
Poster
Thu 6:00 Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming
Daoli Zhu, Lei Zhao
Poster
Thu 7:00 A Nearly-Linear Time Algorithm for Exact Community Recovery in Stochastic Block Model
Peng Wang, Zirui Zhou, Anthony Man-Cho So
Poster
Thu 7:00 Converging to Team-Maxmin Equilibria in Zero-Sum Multiplayer Games
Youzhi Zhang, Bo An
Poster
Thu 7:00 Provable Smoothness Guarantees for Black-Box Variational Inference
Justin Domke
Poster
Thu 7:00 On Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
Di Wang, Hanshen Xiao, Srinivas Devadas, Jinhui Xu
Poster
Thu 7:00 Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Tom Fei, Qiantong Xu, Chengrun Yang
Poster
Thu 7:00 Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks
Marko Vasic, Cameron Chalk, Sarfraz Khurshid, David Soloveichik
Poster
Thu 7:00 Recht-Re Noncommutative Arithmetic-Geometric Mean Conjecture is False
Zehua Lai, Lek-Heng Lim
Poster
Thu 7:00 Efficient Continuous Pareto Exploration in Multi-Task Learning
Pingchuan Ma, Tao Du, Wojciech Matusik
Poster
Thu 7:00 Stochastic Hamiltonian Gradient Methods for Smooth Games
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas
Poster
Thu 7:00 Simultaneous Inference for Massive Data: Distributed Bootstrap
Yang Yu, Shih-Kang Chao, Guang Cheng
Poster
Thu 7:00 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Poster
Thu 7:00 R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
Zhongxiang Dai, Yizhou Chen, Bryan Kian Hsiang Low, Patrick Jaillet , Teck-Hua Ho
Poster
Thu 7:00 Doubly robust off-policy evaluation with shrinkage
Yi Su, Maria Dimakopoulou, Akshay Krishnamurthy, Miro Dudik
Poster
Thu 7:00 Momentum Improves Normalized SGD
Ashok Cutkosky, Harsh Mehta
Poster
Thu 7:00 Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
Michael Zhu, Chang Liu, Jun Zhu
Poster
Thu 7:00 Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush Varshney
Poster
Thu 7:00 Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei
Poster
Thu 7:00 Semi-Supervised Learning with Normalizing Flows
Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Wilson
Poster
Thu 7:00 Online Learning with Imperfect Hints
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit
Poster
Thu 8:00 Principled learning method for Wasserstein distributionally robust optimization with local perturbations
Yongchan Kwon, Wonyoung Kim, Johann Won, Myunghee Cho Paik
Poster
Thu 8:00 Progressive Identification of True Labels for Partial-Label Learning
Jiaqi Lv, Miao Xu, LEI FENG, Gang Niu, Xin Geng, Masashi Sugiyama
Poster
Thu 8:00 Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Poster
Thu 8:00 High-dimensional Robust Mean Estimation via Gradient Descent
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
Poster
Thu 8:00 Generalized and Scalable Optimal Sparse Decision Trees
Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo Seltzer
Poster
Thu 8:00 Coresets for Data-efficient Training of Machine Learning Models
Baharan Mirzasoleiman, Jeff Bilmes, Jure Leskovec
Poster
Thu 8:00 One-shot Distributed Ridge Regression in High Dimensions
Yue Sheng, Edgar Dobriban
Poster
Thu 8:00 Domain Aggregation Networks for Multi-Source Domain Adaptation
Junfeng Wen, Russell Greiner, Dale Schuurmans
Poster
Thu 8:00 Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang
Poster
Thu 8:00 Learning Human Objectives by Evaluating Hypothetical Behavior
Siddharth Reddy, Anca Dragan, Sergey Levine, Shane Legg, Jan Leike
Poster
Thu 8:00 Minimax Pareto Fairness: A Multi Objective Perspective
Natalia Martinez, Martin Bertran, Guillermo Sapiro
Poster
Thu 8:00 SGD Learns One-Layer Networks in WGANs
Qi Lei, Jason Lee, Alex Dimakis, Constantinos Daskalakis
Poster
Thu 8:00 The Performance Analysis of Generalized Margin Maximizers on Separable Data
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Poster
Thu 9:00 Video Prediction via Example Guidance
Jingwei Xu, Harry (Huazhe) Xu, Bingbing Ni, Xiaokang Yang, Prof. Darrell
Poster
Thu 9:00 ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications
Kinjal Basu, Amol Ghoting, Rahul Mazumder, Yao Pan
Poster
Thu 9:00 The Implicit Regularization of Stochastic Gradient Flow for Least Squares
Alnur Ali, Edgar Dobriban, Ryan Tibshirani
Poster
Thu 9:00 Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking
Haoran Sun, Songtao Lu, Mingyi Hong
Poster
Thu 9:00 Decision Trees for Decision-Making under the Predict-then-Optimize Framework
Adam Elmachtoub, Jason Cheuk Nam Liang, Ryan McNellis
Poster
Thu 9:00 On the Global Convergence Rates of Softmax Policy Gradient Methods
Jincheng Mei, Chenjun Xiao, Csaba Szepesvari, Dale Schuurmans
Poster
Thu 9:00 Implicit competitive regularization in GANs
Florian Schaefer, Hongkai Zheng, Anima Anandkumar
Poster
Thu 9:00 Accelerated Message Passing for Entropy-Regularized MAP Inference
Jonathan Lee, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Invited Talk
Thu 10:00 Quantum Machine Learning : Prospects and Challenges
Iordanis Kerenidis
Poster
Thu 12:00 Supervised Quantile Normalization for Low Rank Matrix Factorization
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, JP Vert
Poster
Thu 12:00 Random extrapolation for primal-dual coordinate descent
Ahmet Alacaoglu, Olivier Fercoq, Volkan Cevher
Poster
Thu 12:00 Learning to Rank Learning Curves
Martin Wistuba, Tejaswini Pedapati
Poster
Thu 12:00 Monte-Carlo Tree Search as Regularized Policy Optimization
Jean-Bastien Grill, Florent Altché, Yunhao Tang, Thomas Hubert, Michal Valko, Ioannis Antonoglou, Remi Munos
Poster
Thu 12:00 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
Alexander Shevchenko, Marco Mondelli
Poster
Thu 12:00 Extra-gradient with player sampling for faster convergence in n-player games
Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna
Poster
Thu 12:00 The Complexity of Finding Stationary Points with Stochastic Gradient Descent
Yoel Drori, Ohad Shamir
Poster
Thu 12:00 Composable Sketches for Functions of Frequencies: Beyond the Worst Case
Edith Cohen, Ofir Geri, Rasmus Pagh
Poster
Thu 12:00 Conditional gradient methods for stochastically constrained convex minimization
Maria Vladarean, Ahmet Alacaoglu, Ya-Ping Hsieh, Volkan Cevher
Poster
Thu 12:00 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
Poster
Thu 12:00 Randomized Block-Diagonal Preconditioning for Parallel Learning
Celestine Mendler-Dünner, Aurelien Lucchi
Poster
Thu 13:00 The FAST Algorithm for Submodular Maximization
Adam Breuer, Eric Balkanski, Yaron Singer
Poster
Thu 13:00 A quantile-based approach for hyperparameter transfer learning
David Salinas, Huibin Shen, Valerio Perrone
Poster
Thu 13:00 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks
Fabian Latorre, Paul Rolland, Shaul Nadav Hallak, Volkan Cevher
Poster
Thu 13:00 Modulating Surrogates for Bayesian Optimization
Erik Bodin, Markus Kaiser, Ieva Kazlauskaite, Zhenwen Dai, Neill Campbell, Carl Henrik Ek
Poster
Thu 13:00 On Efficient Low Distortion Ultrametric Embedding
Vincent Cohen-Addad, Karthik C. S., Guillaume Lagarde
Poster
Thu 13:00 Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik
Poster
Thu 13:00 Topic Modeling via Full Dependence Mixtures
Dan Fisher, Mark Kozdoba, Shie Mannor
Poster
Thu 13:00 Teaching with Limited Information on the Learner's Behaviour
Ferdinando Cicalese, Francisco S de Freitas Filho, Eduardo Laber, Marco Molinaro
Poster
Thu 13:00 Spectral Clustering with Graph Neural Networks for Graph Pooling
Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
Poster
Thu 13:00 Preselection Bandits
Viktor Bengs, Eyke Hüllermeier
Poster
Thu 13:00 Projective Preferential Bayesian Optimization
Petrus Mikkola, Milica Todorović, Jari Järvi, Patrick Rinke, Samuel Kaski
Poster
Thu 14:00 From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models
Aytunc Sahin, Yatao Bian, Joachim Buhmann, Andreas Krause
Poster
Thu 14:00 Regularized Optimal Transport is Ground Cost Adversarial
François-Pierre Paty, Marco Cuturi
Poster
Thu 14:00 Parallel Algorithm for Non-Monotone DR-Submodular Maximization
Alina Ene, Huy Nguyen
Poster
Thu 14:00 Anderson Acceleration of Proximal Gradient Methods
Vien Van Mai, Mikael Johansson
Poster
Thu 14:00 Extrapolation for Large-batch Training in Deep Learning
Tao Lin, Lingjing Kong, Sebastian Stich, Martin Jaggi
Poster
Thu 14:00 Optimistic Policy Optimization with Bandit Feedback
Lior Shani, Yonathan Efroni, Aviv Rosenberg, Shie Mannor
Poster
Thu 14:00 Training Binary Neural Networks using the Bayesian Learning Rule
Xiangming Meng, Roman Bachmann, Emti Khan
Poster
Thu 15:00 Stochastic Optimization for Regularized Wasserstein Estimators
Marin Ballu, Quentin Berthet, Francis Bach
Poster
Thu 17:00 Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett
Poster
Thu 17:00 Multi-objective Bayesian Optimization using Pareto-frontier Entropy
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Poster
Thu 17:00 Dual-Path Distillation: A Unified Framework to Improve Black-Box Attacks
Yonggang Zhang, Ya Li, Tongliang Liu, Xinmei Tian
Poster
Thu 17:00 Do We Need Zero Training Loss After Achieving Zero Training Error?
Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama
Poster
Thu 17:00 On the Power of Compressed Sensing with Generative Models
Akshay Kamath, Eric Price, Sushrut Karmalkar
Poster
Thu 17:00 Representation Learning via Adversarially-Contrastive Optimal Transport
Anoop Cherian, Shuchin Aeron
Poster
Thu 17:00 Sparse Subspace Clustering with Entropy-Norm
Liang Bai, Jiye Liang
Poster
Thu 17:00 Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity
Yuanyu Wan, Wei-Wei Tu, Lijun Zhang
Poster
Thu 17:00 Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
Jang-Hyun Kim, Wonho Choo, Hyun Oh Song
Poster
Thu 18:00 On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
Workshop
Fri 1:00 5th ICML Workshop on Human Interpretability in Machine Learning (WHI)
Adrian Weller, Alice Xiang, Amit Dhurandhar, Been Kim, Dennis Wei, Kush Varshney, Umang Bhatt
Workshop
Fri 6:55 Invited Talk: Razvan Pascanu "Continual Learning from an Optimization/Learning-dynamics perspective"
Razvan Pascanu
Workshop
Fri 8:00 Beyond first order methods in machine learning systems
Albert S Berahas, Amir Gholaminejad, Tasos Kyrillidis, Michael Mahoney, Fred Roosta
Workshop
Fri 8:15 Talk by Peter Richtarik - Fast linear convergence of randomized BFGS
Peter Richtarik
Workshop
Fri 8:20 PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks
Ting-wu Chin
Workshop
Fri 8:40 Poster session
Janis Klaise, Lang Liu, Begum Taskazan, Lasse F. Wolff Anthony, Clive Cox, Omid Aramoon, Ting-wu Chin, Alexander Lavin
Workshop
Fri 9:00 Poster Session (click to see links)
Workshop
Fri 9:10 Talk by Francis Bach - Second Order Strikes Back - Globally convergent Newton methods for ill-conditioned generalized self-concordant Losses
Francis Bach
Workshop
Fri 10:30 Spotlight talk 1 - A Second-Order Optimization Algorithm for Solving Problems Involving Group Sparse Regularization
Daniel Robinson
Workshop
Fri 11:00 Talk by Coralia Cartis - Dimensionality reduction techniques for large-scale optimization problems
Coralia Cartis
Workshop
Fri 12:05 Short Talk 4 - Adaptive Regret for Online Control
Edgar Minasyan
Workshop
Fri 12:35 Short Talk 6 - Preference learning along multiple criteria: A game-theoretic perspective
Kush Bhatia
Workshop
Fri 13:30 Spotlight talk 4 - MomentumRNN: Integrating Momentum into Recurrent Neural Networks
HUNG MINH TAN Nguyen
Workshop
Fri 13:50 Spotlight talk 6 - Competitive Mirror Descent
Florian Schaefer
Workshop
Fri 14:00 Industry Panel - Talk by Boris Ginsburg - Large scale deep learning: new trends and optimization challenges
Boris Ginsburg
Workshop
Fri 14:15 Industry Panel - Talk by Jonathan Hseu - ML Models in Production
Jonathan Hseu
Workshop
Fri 15:30 Talk by Rachel Ward - Weighted Optimization: better generalization by smoother interpolation
Rachel Ward
Workshop
Sat 5:00 Negative Dependence and Submodularity: Theory and Applications in Machine Learning
Zelda Mariet, Michal Derezinski, Mike Gartrell
Workshop
Sat 5:50 Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
Jian Tang, Le Song, Jure Leskovec, Renjie Liao, Yujia Li, Sanja Fidler, Richard Zemel, Russ Salakhutdinov
Workshop
Sat 6:00 7th ICML Workshop on Automated Machine Learning (AutoML 2020)
Frank Hutter, Joaquin Vanschoren, Marius Lindauer, Charles Weill, Katharina Eggensperger, Matthias Feurer
Workshop
Sat 6:45 Contributed Talk 1: Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits
Jack Parker-Holder, Vu Nguyen, Stephen Roberts
Workshop
Sat 7:00 Real World Experiment Design and Active Learning
Ilija Bogunovic, Willie Neiswanger, Yisong Yue
Workshop
Sat 7:10 1.4 Multi-Source Unsupervised Hyperparameter Optimization
Masahiro Nomura
Workshop
Sat 7:10 1.3 Cost-Aware Bayesian Optimization
Eric Lee
Workshop
Sat 7:15 "Latent Space Optimization with Deep Generative Models"
Jose Miguel Hernandez-Lobato
Workshop
Sat 7:15 1.9 Bayesian optimization for Iterative Learning
Vu Nguyen
Workshop
Sat 7:20 1.11 Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization
Sauptik Dhar
Workshop
Sat 7:45 Negative Dependence and Sampling
Stefanie Jegelka
Workshop
Sat 8:40 Contributed Talk 2: Bayesian Optimization with Fairness Constraints
Valerio Perrone
Workshop
Sat 9:00 Optimal Query Complexity of Secure Stochastic Convex Optimization by Wei Tang
Workshop
Sat 9:30 Efficient Privacy-Preserving Stochastic Nonconvex Optimization by Lingxiao Wang
Workshop
Sat 10:15 Exponentially Faster Algorithms for Machine Learning
Yaron Singer
Workshop
Sat 10:45 To Call or not to Call? Using ML Prediction APIs more Accurately and Economically by Lingjiao Chen
Workshop
Sat 10:50 Searching for Diverse Biological Sequences
Lucy Colwell
Workshop
Sat 11:25 Constrained Maximization of Lattice Submodular Functions
Aytunc Sahin, Joachim Buhmann, Andreas Krause
Workshop
Sat 12:00 2.10 Uncertainty aware Search framework for Multi-Objective Bayesian Optimization with Constraints
Syrine Belakaria
Workshop
Sat 12:05 2.13 Bayesian Optimization for real-time, automatic design of face stimuli in human-centred research
Pedro F da Costa
Workshop
Sat 12:50 Lightning Talks Session 2
Jichan Chung, Saurav Prakash, Misha Khodak, Ravi Rahman, Vaikkunth Mugunthan, xinwei zhang, Hossein Hosseini
Workshop
Sat 14:00 Keynote Session 5: Advances and Open Problems in Federated Learning, by Brendan McMahan (Google)
Brendan McMahan
Workshop
(#51 / Sess. 1) Deep Lagrangian Propagation in Graph Neural Networks
Matteo Tiezzi
Workshop
Poster presentation: Relative gradient optimization of the Jacobian term in unsupervised deep learning
Invertible Workshop INNF
Workshop
(#93 / Sess. 1) Geoopt: Riemannian Optimization in PyTorch
Max Kochurov
Workshop
(#94 / Sess. 2) Are Hyperbolic Representations in Graphs Created Equal?
Max Kochurov
Workshop
(#96 / Sess. 1) Active Learning on Graphs via Meta Learning
Kaushalya Madhawa
Workshop
Maximum Entropy Model Rollouts: Fast Model Based Policy Optimization without Compounding Errors
Chi Zhang
Workshop
On the Equivalence of Bi-Level Optimization and Game-Theoretic Formulations of Invariant Risk Minimization
Kartik Ahuja
Workshop
MOPO: Model-based Offline Policy Optimization
Tianhe Yu
Workshop
Efficient Imitation Learning with Local Trajectory Optimization
Jialin Song