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[ Algorithms ] [ Algorithms, Optimization and Computation Methods ] [ Algorithms; Algorithms ] [ Applications ] [ Data, Challenges, Implementations, and Software ] [ Deep Learning ] [ Ethics and Safety ] [ Learning Theory and Statistics ] [ Models and Methods ] [ Neuroscience and Cognitive Science ] [ Optimization ] [ Probabilistic Methods ] [ Reinforcement Learning ] [ Reinforcement Learning and Planning ] [ Theory ]

Topic Keywords

[ Accountability, Transparency and Interpretability ] [ Active Learning ] [ Active Learning ] [ Adversarial Examples ] [ Adversarial Learning ] [ Approximate Inference ] [ Architectures ] [ Asymptotic statistics ] [ Attention Models ] [ Audio and Speech Processing ] [ AutoML ] [ Bandit Algorithms ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandit Algorithms; Theory ] [ Bayesian Methods ] [ Bayesian Nonparametrics ] [ Biologically Plausible Deep Networks ] [ Biology and Genomics ] [ Body Pose, Face, and Gesture Analysis ] [ Causal Inference ] [ Causality ] [ Classification ] [ Classification ] [ Classification; Algorithms ] [ Classification; Applications ] [ Classification; Deep Learning ] [ Classification; Deep Learning ] [ Clustering ] [ Clustering; Theory ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Deep Learning ] [ Combinatorial Optimization ] [ Compressed Sensing and Sparse Coding ] [ Computational Learning Theory ] [ Computer Vision ] [ Computer Vision; Applications ] [ Computer Vision; Deep Learning ] [ Continual learning ] [ Convex optimization ] [ Data Compression ] [ Data Sets or Data Repositories ] [ Decision Processes and Bandits ] [ Decision Theory ] [ Deep Learning ] [ Denoising ] [ Denoising; Applications ] [ Denoising; Theory ] [ Density Estimation ] [ Dimension Reduction and Components Analysis ] [ Discrete Optimization ] [ Distributed Inference ] [ Efficient Training Methods ] [ Embedding Approaches ] [ Ensemble Methods ] [ Exploration ] [ Fairness, Accountability, and Transparency ] [ Fairness, Equity, Justice, and Safety ] [ Feature Selection ] [ Few-Shot Learning ] [ Frequentist Methods ] [ Game Theory and Computational Economics ] [ Game Theory and Mechanism Design ] [ Gaussian Processes ] [ Generative and Latent Variable Models ] [ Generative Models ] [ Generative Models and Autoencoders ] [ Gradient-Based Optimization ] [ Graphical Models ] [ Graph Neural Networks ] [ Hardware and Systems ] [ High-dimensional Statistics ] [ Human or Animal Learning; Probabilistic Methods ] [ Image Segmentation ] [ Information Retrieval ] [ Information Theory ] [ Interpretable Statistics and Machine Learning ] [ Kernel Methods ] [ Large Deviations and Asymptotic Analysis ] [ Large Scale Learning ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Optimization ] [ Large Scale, Parallel and Distributed ] [ Learning on Graphs ] [ Learning Theory ] [ Matrix and Tensor Factorization ] [ Medical Imaging and Informatics ] [ Memory ] [ Meta-Learning ] [ Missing Data ] [ Missing Data ] [ Missing Data; Algorithms ] [ Model Selection ] [ Monte Carlo Methods ] [ Multi-agent systems ] [ Multi-task and transfer learning ] [ Navigation ] [ Network Analysis ] [ Neuroscience ] [ Nonconvex Optimization ] [ Non-Convex Optimization ] [ Nonlinear Dimensionality Reduction and Manifold Learning ] [ Nonlinear Dimensionality Reduction and Manifold Learning; Deep Learning ] [ Nonlinear Embedding and Manifold Learning ] [ Nonparametric Models ] [ Online Learning ] [ Online Learning ] [ Online Learning; Optimization ] [ Optimization for Neural Networks ] [ Other Applications ] [ Other Deep Learning ] [ Other Probabilistic Methods ] [ Other Theory / Statistics ] [ Planning and Control ] [ Plasticity and Adaptation ] [ Privacy, Anonymity, and Security ] [ Privacy-preserving Statistics and Machine Learning ] [ Probabilistic Programming ] [ Problem Solving ] [ Regression; Algorithms ] [ Regression; Optimization ] [ Regression; Probabilistic Methods; Probabilistic Methods ] [ Reinforcement Learning ] [ Reinforcement Learning ] [ Reinforcement Learning ] [ Representation Learning ] [ Representation Learning; Applications ] [ Robustness ] [ Robust Statistics and Machine Learning ] [ Sampling ] [ Semi-supervised learning ] [ Semi-Supervised Learning ] [ Semi-Supervised Learning; Applications ] [ Semi-Supervised Learning; Deep Learning ] [ Signal Processing ] [ Societal Impacts of Machine Learning ] [ Spatial or Spatio-temporal Model ] [ Spectral Methods ] [ Statistical Learning Theory ] [ Stochastic Methods ] [ Structured Prediction and Learning ] [ Supervised Learning ] [ Theory ] [ Theory ] [ Time Series and Sequence Models ] [ Trustworthy Machine Learning ] [ Uncertainty Estimation ] [ Unsupervised ] [ Unsupervised Learning ] [ Unsupervised Learning ] [ Unsupervised Learning; Applications ] [ Unsupervised Learning; Applications ] [ Variational Inference ] [ Video Analysis ] [ Visualization or Exposition Techniques for Deep Networks ] [ Visual Perception ] [ Visual Question Answering ]

537 Results

Remarks
Tue 8:45 Opening Remarks
Arindam Banerjee, Kenji Fukumizu
Invited Talk
Tue 9:00 Reliable Predictions? Counterfactual Predictions? Equitable Treatment? Some Recent Progress in Predictive Inference
Emmanuel Candes
Oral
Tue 10:30 Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Fred Kunstner, Raunak Kumar, Mark Schmidt
Oral Session
Tue 10:30 Theory of Statistical and Deep Learning Methods
Oral
Tue 10:45 Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
Leena Chennuru Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar
Oral
Tue 11:00 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth
Oral
Tue 11:15 Stable ResNet
Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau
Oral Session
Tue 11:30 Sampling Methods
Oral
Tue 11:30 Couplings for Multinomial Hamiltonian Monte Carlo
Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge
Oral
Tue 11:45 An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo
Matthew Hoffman, Alexey Radul, Pavel Sountsov
Oral
Tue 12:00 Maximal Couplings of the Metropolis-Hastings Algorithm
Guanyang Wang, John O'Leary, Pierre Jacob
Oral
Tue 12:15 GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding, Constantinos Daskalakis, Soheil Feizi
Affinity Event
Tue 12:30 WiML and Caucus for Women in Statistics
Tatjana Chavdarova, Sarah Tan, Jessica Kohlschmidt
Mentorship
Tue 12:30 Mentorship Session 1
Poster
Tue 14:00 Active Learning under Label Shift
Eric Zhao, Angie Liu, Animashree Anandkumar, Yisong Yue
Poster
Tue 14:00 Regression Discontinuity Design under Self-selection
Sida Peng, Yang Ning
Poster
Tue 14:00 Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
Yixing Zhang, Xiuyuan Cheng, Galen Reeves
Poster
Tue 14:00 Revisiting Model-Agnostic Private Learning: Faster Rates and Active Learning
Chong Liu, Yuqing Zhu, Kamalika Chaudhuri, Yu-Xiang Wang
Poster
Tue 14:00 Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC
Priyank Jaini, Didrik Nielsen, Max Welling
Poster
Tue 14:00 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei
Poster
Tue 14:00 Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering
Sebastian Macaluso, Craig Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum
Poster
Tue 14:00 Alternating Direction Method of Multipliers for Quantization
Tianjian Huang, Prajwal Singhania, Maziar Sanjabi, Pabitra Mitra, Meisam Razaviyayn
Poster
Tue 14:00 Maximizing Agreements for Ranking, Clustering and Hierarchical Clustering via MAX-CUT
Vaggos Chatziafratis, Mohammad Mahdian, Sara Ahmadian
Poster
Tue 14:00 Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function
Ioannis Tsaknakis, Mingyi Hong
Poster
Tue 14:00 Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences
Sreejith Sreekumar, Zhengxin Zhang, Ziv Goldfeld
Poster
Tue 14:00 Differentiable Greedy Algorithm for Monotone Submodular Maximization: Guarantees, Gradient Estimators, and Applications
Shinsaku Sakaue
Poster
Tue 14:00 Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani
Poster
Tue 14:00 On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
Youssef Mroueh, Truyen Nguyen
Poster
Tue 14:00 Sample Elicitation
Jiaheng Wei, Zuyue Fu, Yang Liu, Xingyu Li, Zhuoran Yang, Zhaoran Wang
Poster
Tue 14:00 Detection and Defense of Topological Adversarial Attacks on Graphs
Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates
Poster
Tue 14:00 Dynamic Cutset Networks
Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate
Poster
Tue 14:00 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning
Hitesh Sapkota, Yiming Ying, Feng Chen, Qi Yu
Poster
Tue 14:00 The Base Measure Problem and its Solution
Alexey Radul, Boris Alexeev
Poster
Tue 14:00 Differentially Private Online Submodular Maximization
Sebastian Perez-Salazar, Rachel Cummings
Poster
Tue 14:00 Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes
Nhuong Nguyen, Toan Nguyen, PHUONG HA NGUYEN, Quoc Tran-Dinh, Lam Nguyen, Marten van Dijk
Poster
Tue 14:00 Reinforcement Learning for Mean Field Games with Strategic Complementarities
Kiyeob Lee, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai
Poster
Tue 14:00 Differentiable Causal Discovery Under Unmeasured Confounding
Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky, Ilya Shpitser
Poster
Tue 14:00 Shapley Flow: A Graph-based Approach to Interpreting Model Predictions
Jiaxuan Wang, Jenna Wiens, Scott Lundberg
Poster
Tue 14:00 An Optimal Reduction of TV-Denoising to Adaptive Online Learning
Dheeraj Baby, Xuandong Zhao, Yu-Xiang Wang
Poster
Tue 14:00 The Sample Complexity of Meta Sparse Regression
Zhanyu Wang, Jean Honorio
Poster
Tue 14:00 Nonparametric Variable Screening with Optimal Decision Stumps
Jason Klusowski, Peter M Tian
Poster
Tue 14:00 Sharp Analysis of a Simple Model for Random Forests
Jason Klusowski
Poster
Tue 14:00 Deep Spectral Ranking
ILKAY YILDIZ, Jennifer Dy, Deniz Erdogmus, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis
Poster
Tue 14:00 Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin, Yu Bai, Yu-Xiang Wang
Poster
Tue 14:00 A constrained risk inequality for general losses
John Duchi, Feng Ruan
Poster
Tue 14:00 Training a Single Bandit Arm
Eren Ozbay, Vijay Kamble
Poster
Tue 14:00 Inductive Mutual Information Estimation: A Convex Maximum-Entropy Copula Approach
Yves-Laurent Kom Samo
Poster
Tue 14:00 Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty
Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian
Poster
Tue 14:00 Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms
Tengyu Xu, Yingbin Liang
Poster
Tue 14:00 The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain
Fergus Simpson, Alexis Boukouvalas, Vaclav Cadek, Elvijs Sarkans, Nicolas Durrande
Poster
Tue 14:00 On Learning Continuous Pairwise Markov Random Fields
Abhin Shah, Devavrat Shah, Gregory Wornell
Poster
Tue 14:00 Non-Stationary Off-Policy Optimization
Joey Hong, Brano Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed
Poster
Tue 14:00 An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling
QIN DING, Cho-Jui Hsieh, James Sharpnack
Poster
Tue 14:00 Learning with Gradient Descent and Weakly Convex Losses
Dominic Richards, Mike Rabbat
Poster
Tue 14:00 Associative Convolutional Layers
Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh Gupta
Poster
Tue 14:00 Influence Decompositions For Neural Network Attribution
Kyle Reing, Greg Ver Steeg, Aram Galstyan
Poster
Tue 14:00 On the Privacy Properties of GAN-generated Samples
Zinan Lin, Vyas Sekar, Giulia Fanti
Poster
Tue 14:00 Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case
Yufeng Zhang, Zhuoran Yang, Zhaoran Wang
Poster
Tue 14:00 Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
Jelena Diakonikolas, Constantinos Daskalakis, Michael Jordan
Poster
Tue 14:00 Problem-Complexity Adaptive Model Selection for Stochastic Linear Bandits
Avishek Ghosh, Abishek Sankararaman, Ramchandran Kannan
Poster
Tue 14:00 A Hybrid Approximation to the Marginal Likelihood
Eric Chuu, Debdeep Pati, Anirban Bhattacharya
Poster
Tue 14:00 TenIPS: Inverse Propensity Sampling for Tensor Completion
Chengrun Yang, Lijun Ding, Ziyang Wu, Madeleine Udell
Poster Session
Tue 14:00 Poster Session 1
Poster
Tue 14:00 Improving Classifier Confidence using Lossy Label-Invariant Transformations
Sooyong Jang, Insup Lee, James Weimer
Poster
Tue 14:00 Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden, John Duchi, Gregory Valiant
Poster
Tue 14:00 Active Online Learning with Hidden Shifting Domains
Yining Chen, Haipeng Luo, Tengyu Ma, Chicheng Zhang
Poster
Tue 14:00 Fast Statistical Leverage Score Approximation in Kernel Ridge Regression
Yifan Chen, Yun Yang
Poster
Tue 14:00 Designing Transportable Experiments Under S-admissability
My Phan, David Arbour, Drew Dimmery, Anup Rao
Poster
Tue 14:00 Semi-Supervised Learning with Meta-Gradient
Taihong Xiao, Xin-Yu Zhang, Haolin Jia, Ming-Ming Cheng, Ming-Hsuan Yang
Poster
Tue 14:00 Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Yu Gong, Hossein Hajimirsadeghi, Jiawei He, Thibaut Durand, Greg Mori
Poster
Tue 14:00 Density of States Estimation for Out of Distribution Detection
Warren Morningstar, Cusuh Ham, Andrew Gallagher, Balaji Lakshminarayanan, Alex Alemi, Joshua Dillon
Poster
Tue 14:00 Principal Subspace Estimation Under Information Diffusion
Fan Zhou, Ping Li, Zhixin Zhou
Poster
Tue 14:00 Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel Augusto Ramos Macedo Antunes de Souza, Diego Mesquita, João Paulo Gomes, César Lincoln Mattos
Poster
Tue 14:00 Generalization of Quasi-Newton Methods: Application to Robust Symmetric Multisecant Updates
Damien Scieur, Lewis Liu, Thomas Pumir, Nicolas Boumal
Poster
Tue 14:00 Random Coordinate Underdamped Langevin Monte Carlo
Zhiyan Ding, Qin Li, Jianfeng Lu, Stephen Wright
Poster
Tue 14:00 Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo
Poster
Tue 14:00 Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.
Neil Jethani, Mukund Sudarshan, Yindalon Aphinyanaphongs, Rajesh Ranganath
Poster
Tue 14:00 List Learning with Attribute Noise
Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie
Poster
Tue 14:00 Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis
Poster
Tue 14:00 Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary Charles, Jakub Konečný
Poster
Tue 14:00 Matérn Gaussian Processes on Graphs
Slava Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Deisenroth, Nicolas Durrande
Poster
Tue 14:00 Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
Mayee Chen, Benjamin Cohen-Wang, Stephen Mussmann, Fred Sala, Christopher Re
Poster
Tue 14:00 Accumulations of Projections—A Unified Framework for Random Sketches in Kernel Ridge Regression
Yifan Chen, Yun Yang
Poster
Tue 14:00 Counterfactual Representation Learning with Balancing Weights
Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin Duke
Poster
Tue 14:00 Accelerating Metropolis-Hastings with Lightweight Inference Compilation
Feynman Liang, Nimar Arora, Nazanin Tehrani, Yucen Li, Michael Tingley, Erik Meijer
Poster
Tue 14:00 Algorithms for Fairness in Sequential Decision Making
Min Wen, Osbert Bastani, Ufuk Topcu
Poster
Tue 14:00 Simultaneously Reconciled Quantile Forecasting of Hierarchically Related Time Series
Xing Han, Sambarta Dasgupta, Joydeep Ghosh
Poster
Tue 14:00 Competing AI: How does competition feedback affect machine learning?
Tony Ginart, Eva Zhang, Yongchan Kwon, James Zou
Poster
Tue 14:00 A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
Thang Doan, Mehdi Abbana Bennani, Bogdan Mazoure, Guillaume Rabusseau, Pierre Alquier
Poster
Tue 14:00 No-Regret Algorithms for Private Gaussian Process Bandit Optimization
Abhimanyu Dubey
Poster
Tue 14:00 On the Linear Convergence of Policy Gradient Methods for Finite MDPs
Jalaj Bhandari, Daniel Russo
Poster
Tue 14:00 SONIA: A Symmetric Blockwise Truncated Optimization Algorithm
Majid Jahani, MohammadReza Nazari, Rachael Tappenden, Albert Berahas, Martin Takac
Poster
Tue 14:00 A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu, Shiyun Xu, Kan Chen
Poster
Tue 14:00 Differentially Private Weighted Sampling
Edith Cohen, Ofir Geri, Tamas Sarlos, Uri Stemmer
Poster
Tue 14:00 Learning the Truth From Only One Side of the Story
Heinrich Jiang, Qijia Jiang, Aldo Pacchiano
Poster
Tue 14:00 Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks
Huichen Li, Linyi Li, Xiaojun Xu, Xiaolu Zhang, Shuang Yang, Bo Li
Poster
Tue 14:00 Multitask Bandit Learning Through Heterogeneous Feedback Aggregation
Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel Riek, Kamalika Chaudhuri
Poster
Tue 14:00 Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath, Akilesh Tangella, Danica Sutherland, Nathan Srebro
Poster
Tue 14:00 Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
Shengjia Zhao, Stefano Ermon
Poster
Tue 14:00 Fast Adaptation with Linearized Neural Networks
Wesley Maddox, Shuai Tang, Pablo Moreno, Andrew Gordon Wilson, Andreas Damianou
Poster
Tue 14:00 Online Robust Control of Nonlinear Systems with Large Uncertainty
Dimitar Ho, Hoang Le, John Doyle, Yisong Yue
Poster
Tue 14:00 Animal pose estimation from video data with a hierarchical von Mises-Fisher-Gaussian model
Libby Zhang, Tim Dunn, Jesse Marshall, Bence Olveczky, Scott Linderman
Poster
Tue 14:00 Sketch based Memory for Neural Networks
Rina Panigrahy, Xin Wang, Manzil Zaheer
Poster
Tue 14:00 Online Model Selection for Reinforcement Learning with Function Approximation
Jonathan Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
Poster
Tue 14:00 Efficient Interpolation of Density Estimators
Paxton Turner, Jingbo Liu, Philippe Rigollet
Oral Session
Tue 16:15 Bandits, Reinforcement Learning / Optimization
Oral
Tue 16:15 Federated Multi-armed Bandits with Personalization
Chengshuai Shi, Cong Shen, Jing Yang
Oral
Tue 16:30 Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
Ming Yin, Yu Bai, Yu-Xiang Wang
Oral
Tue 16:45 Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic
Oral
Tue 17:00 Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective
Jacky Zhang, Rajiv Khanna, Anastasios Kyrillidis, Sanmi Koyejo
Oral
Tue 17:15 Entropy Partial Transport with Tree Metrics: Theory and Practice
Tam Le, Truyen Nguyen
Oral Session
Tue 17:15 Theory and Practice of Machine Learning
Oral
Tue 17:30 Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvarinen
Oral
Tue 17:45 Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi Wang, Shengyang Sun, Roger Grosse
Oral
Tue 18:00 A Variational Information Bottleneck Approach to Multi-Omics Data Integration
Changhee Lee, Mihaela van der Schaar
Poster
Tue 18:30 Consistent k-Median: Simpler, Better and Robust
Xiangyu Guo, Janardhan Kulkarni, Shi Li, Jiayi Xian
Poster
Tue 18:30 Linear Models are Robust Optimal Under Strategic Behavior
Wei Tang, Chien-Ju Ho, Yang Liu
Poster
Tue 18:30 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka
Poster
Tue 18:30 Prediction with Finitely many Errors Almost Surely
Changlong Wu, Narayana Santhanam
Poster
Tue 18:30 Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees
Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen Bach
Poster
Tue 18:30 Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference
Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David Dunson, Debdeep Pati
Poster
Tue 18:30 Contrastive learning of strong-mixing continuous-time stochastic processes
Bingbin Liu, Pradeep Ravikumar, Andrej Risteski
Poster
Tue 18:30 Maximal Couplings of the Metropolis-Hastings Algorithm
Guanyang Wang, John O'Leary, Pierre Jacob
Poster
Tue 18:30 Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms
Tianyu Ding, Zhihui Zhu, Manolis Tsakiris, Rene Vidal, Daniel Robinson
Poster
Tue 18:30 Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship
Abishek Sankararaman, Soumya Basu, Karthik Abinav Sankararaman
Poster
Tue 18:30 Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar
Poster
Tue 18:30 Online Forgetting Process for Linear Regression Models
Yuantong Li, Chi-Hua Wang, Guang Cheng
Poster
Tue 18:30 Meta Learning in the Continuous Time Limit
Ruitu Xu, Lin Chen, Amin Karbasi
Poster
Tue 18:30 Causal Modeling with Stochastic Confounders
Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze Yun Leong
Poster
Tue 18:30 Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David Blei, John Cunningham
Poster
Tue 18:30 Federated Multi-armed Bandits with Personalization
Chengshuai Shi, Cong Shen, Jing Yang
Poster
Tue 18:30 Differentially Private Monotone Submodular Maximization Under Matroid and Knapsack Constraints
Omid Sadeghi, Maryam Fazel
Poster
Tue 18:30 Causal Inference with Selectively Deconfounded Data
Kyra Gan, Andrew Li, Zachary Lipton, Sridhar Tayur
Poster
Tue 18:30 Tractable contextual bandits beyond realizability
Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey
Poster
Tue 18:30 Learning Shared Subgraphs in Ising Model Pairs
Burak Varici, Saurabh Sihag, Ali Tajer
Poster
Tue 18:30 A comparative study on sampling with replacement vs Poisson sampling in optimal subsampling
HaiYing Wang, Jiahui Zou
Poster
Tue 18:30 Robust Imitation Learning from Noisy Demonstrations
Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama
Poster
Tue 18:30 vqSGD: Vector Quantized Stochastic Gradient Descent
Venkata Gandikota, Daniel Kane, Raj Kumar Maity, Arya Mazumdar
Poster
Tue 18:30 Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers
Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps
Poster
Tue 18:30 Graph Gamma Process Linear Dynamical Systems
Rahi Kalantari, Mingyuan Zhou
Poster
Tue 18:30 Adversarially Robust Estimate and Risk Analysis in Linear Regression
Yue Xing, Ruizhi Zhang, Guang Cheng
Poster
Tue 18:30 The Spectrum of Fisher Information of Deep Networks Achieving Dynamical Isometry
Tomohiro Hayase, Ryo Karakida
Poster
Tue 18:30 Understanding the wiring evolution in differentiable neural architecture search
Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin
Poster
Tue 18:30 A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits
Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi
Poster
Tue 18:30 Tight Regret Bounds for Infinite-armed Linear Contextual Bandits
Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou
Poster
Tue 18:30 Minimax Estimation of Laplacian Constrained Precision Matrices
Jiaxi Ying, José Vinícius de Miranda Cardoso , Daniel Palomar
Poster
Tue 18:30 Entropy Partial Transport with Tree Metrics: Theory and Practice
Tam Le, Truyen Nguyen
Poster
Tue 18:30 On the Absence of Spurious Local Minima in Nonlinear Low-Rank Matrix Recovery Problems
Yingjie Bi, Javad Lavaei
Poster
Tue 18:30 One-Round Communication Efficient Distributed M-Estimation
Yajie Bao, Weijia Xiong
Poster
Tue 18:30 Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
Hunter Lang, Aravind Reddy Talla, David Sontag, Aravindan Vijayaraghavan
Poster
Tue 18:30 Understanding Gradient Clipping In Incremental Gradient Methods
Jiang Qian, Yuren Wu, Bojin Zhuang, Shaojun Wang, Jing Xiao
Poster
Tue 18:30 Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic
Poster
Tue 18:30 Taming heavy-tailed features by shrinkage
Ziwei Zhu, Wenjing Zhou
Poster
Tue 18:30 Regularized Policies are Reward Robust
Hisham Husain, Kamil Ciosek, Ryota Tomioka
Poster
Tue 18:30 GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences
Mucong Ding, Constantinos Daskalakis, Soheil Feizi
Poster
Tue 18:30 DAG-Structured Clustering by Nearest Neighbors
Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum
Poster
Tue 18:30 γ-ABC: Outlier-Robust Approximate Bayesian Computation Based on a Robust Divergence Estimator
Masahiro Fujisawa, Takeshi Teshima, Issei Sato, Masashi Sugiyama
Poster
Tue 18:30 Tracking Regret Bounds for Online Submodular Optimization
Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka
Poster
Tue 18:30 Good Classifiers are Abundant in the Interpolating Regime
Ryan Theisen, Jason Klusowski, Michael Mahoney
Poster
Tue 18:30 Predictive Power of Nearest Neighbors Algorithm under Random Perturbation
Yue Xing, Qifan Song, Guang Cheng
Poster
Tue 18:30 On the Generalization Properties of Adversarial Training
Yue Xing, Qifan Song, Guang Cheng
Poster
Tue 18:30 Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation
Han Bao, Masashi Sugiyama
Poster
Tue 18:30 On the Faster Alternating Least-Squares for CCA
Zhiqiang Xu, Ping Li
Poster
Tue 18:30 Gradient Descent in RKHS with Importance Labeling
Tomoya Murata, Taiji Suzuki
Poster
Tue 18:30 Independent Innovation Analysis for Nonlinear Vector Autoregressive Process
Hiroshi Morioka, Hermanni Hälvä, Aapo Hyvarinen
Poster
Tue 18:30 Generalization Bounds for Stochastic Saddle Point Problems
Junyu Zhang, Mingyi Hong, Mengdi Wang, Shuzhong Zhang
Poster
Tue 18:30 One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks
Hanjing Zhu, Jiaming Xu
Poster
Tue 18:30 Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent
Fred Kunstner, Raunak Kumar, Mark Schmidt
Poster
Tue 18:30 Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning
Yunhao Tang, Alp Kucukelbir
Poster
Tue 18:30 Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Vo Nguyen Le Duy, Ichiro Takeuchi
Poster
Tue 18:30 Q-learning with Logarithmic Regret
Kunhe Yang, Lin Yang, Simon Du
Poster
Tue 18:30 Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
Zheng Wang, Wei Xing, Robert Kirby, Shandian Zhe
Poster
Tue 18:30 On the Suboptimality of Negative Momentum for Minimax Optimization
Guodong Zhang, Yuanhao Wang
Poster
Tue 18:30 Learning Temporal Point Processes with Intermittent Observations
Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De
Poster
Tue 18:30 CADA: Communication-Adaptive Distributed Adam
Tianyi Chen, Ziye Guo, Yuejiao Sun, Wotao Yin
Poster
Tue 18:30 Corralling Stochastic Bandit Algorithms
Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
Poster
Tue 18:30 Bandit algorithms: Letting go of logarithmic regret for statistical robustness
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna Jagannathan
Poster
Tue 18:30 Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features
Shingo Yashima, Atsushi Nitanda, Taiji Suzuki
Poster
Tue 18:30 Tensor Networks for Probabilistic Sequence Modeling
Jacob E Miller, Guillaume Rabusseau, John Terilla
Poster
Tue 18:30 Stability and Risk Bounds of Iterative Hard Thresholding
Xiaotong Yuan, Ping Li
Poster
Tue 18:30 Minimax Model Learning
Cameron Voloshin, Nan Jiang, Yisong Yue
Poster
Tue 18:30 On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification
Darren Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, Michael Jordan
Poster Session
Tue 18:30 Poster Session 2
Poster
Tue 18:30 Flow-based Alignment Approaches for Probability Measures in Different Spaces
Tam Le, Nhat Ho, Makoto Yamada
Poster
Tue 18:30 Identification of Matrix Joint Block Diagonalization
Yunfeng Cai, Ping Li
Poster
Tue 18:30 Learning with risk-averse feedback under potentially heavy tails
Matthew Holland, El Mehdi Haress
Poster
Tue 18:30 Experimental Design for Regret Minimization in Linear Bandits
Andrew Wagenmaker, Julian Katz-Samuels, Kevin Jamieson
Poster
Tue 18:30 Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima
Poster
Tue 18:30 Shadow Manifold Hamiltonian Monte Carlo
Chris van der Heide, Fred Roosta, Liam Hodgkinson, Dirk Kroese
Poster
Tue 18:30 Unifying Clustered and Non-stationary Bandits
Chuanhao Li, Qingyun Wu, Hongning Wang
Poster
Tue 18:30 Optimal query complexity for private sequential learning against eavesdropping
Jiaming Xu, Kuang Xu, Dana Yang
Poster
Tue 18:30 Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato
Poster
Tue 18:30 Mirror Descent View for Neural Network Quantization
Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr, RICHARD HARTLEY, Puneet Dokania
Poster
Tue 18:30 Ridge Regression with Over-parametrized Two-Layer Networks Converge to Ridgelet Spectrum
Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
Poster
Tue 18:30 Robustness and scalability under heavy tails, without strong convexity
Matthew Holland
Poster
Tue 18:30 Beyond Marginal Uncertainty: How Accurately can Bayesian Regression Models Estimate Posterior Predictive Correlations?
Chaoqi Wang, Shengyang Sun, Roger Grosse
Poster
Tue 18:30 On the High Accuracy Limitation of Adaptive Property Estimation
Yanjun Han
Poster
Tue 18:30 Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers
Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Poster
Tue 18:30 Bayesian Model Averaging for Causality Estimation and its Approximation based on Gaussian Scale Mixture Distributions
Shunsuke Horii
Poster
Tue 18:30 Regret Minimization for Causal Inference on Large Treatment Space
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Poster
Tue 18:30 Sample efficient learning of image-based diagnostic classifiers via probabilistic labels
Roberto Vega, Pouneh Gorji, Zichen Zhang, Xuebin Qin, Abhilash Rakkunedeth, Jeevesh Kapur, Jacob Jaremko, Russell Greiner
Poster
Tue 18:30 Mean-Variance Analysis in Bayesian Optimization under Uncertainty
Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi
Poster
Tue 18:30 Revisiting the Role of Euler Numerical Integration on Acceleration and Stability in Convex Optimization
Peiyuan Zhang, Antonio Orvieto, Hadi Daneshmand, Thomas Hofmann, Roy S. Smith
Poster
Tue 18:30 RankDistil: Knowledge Distillation for Ranking
Sashank Reddi, Rama Kumar Pasumarthi, Aditya Menon, Ankit Singh Rawat, Felix Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar
Poster
Tue 18:30 Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo
Poster
Tue 18:30 Minimal enumeration of all possible total effects in a Markov equivalence class
Richard Guo, Ema Perkovic
Poster
Tue 18:30 No-Regret Reinforcement Learning with Heavy-Tailed Rewards
Vincent Zhuang, Yanan Sui
Mentorship
Tue 20:30 Mentorship Session 2
Affinity Event
Wed 4:00 Black in AI
Sanmi Koyejo
Mentorship
Wed 4:00 Mentorship Session 3
Poster
Wed 6:00 Regularized ERM on random subspaces
Andrea Della Vecchia, Jaouad Mourtada, Ernesto De Vito, Lorenzo Rosasco
Poster
Wed 6:00 Calibrated Adaptive Probabilistic ODE Solvers
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Poster
Wed 6:00 Top-m identification for linear bandits
Clémence Réda, Emilie Kaufmann, Andrée Delahaye-Duriez
Poster
Wed 6:00 On the Effect of Auxiliary Tasks on Representation Dynamics
Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney
Poster
Wed 6:00 On the proliferation of support vectors in high dimensions
Daniel Hsu, Vidya Muthukumar, Ji Xu
Poster
Wed 6:00 Unconstrained MAP Inference, Exponentiated Determinantal Point Processes, and Exponential Inapproximability
Naoto Ohsaka
Poster
Wed 6:00 Graphical Normalizing Flows
Antoine Wehenkel, Gilles Louppe
Poster
Wed 6:00 Fully Gap-Dependent Bounds for Multinomial Logit Bandit
Jiaqi Yang
Poster
Wed 6:00 An Analysis of LIME for Text Data
Dina Mardaoui, Damien Garreau
Poster
Wed 6:00 A Bayesian nonparametric approach to count-min sketch under power-law data streams
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
Poster
Wed 6:00 Nonlinear Functional Output Regression: A Dictionary Approach
Dimitri Bouche, Marianne Clausel, François Roueff, Florence d'Alché-Buc
Poster
Wed 6:00 Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
JJ Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
Poster
Wed 6:00 Collaborative Classification from Noisy Labels
Lucas Maystre, Nagarjuna Kumarappan, Judith Bütepage, Mounia Lalmas
Poster
Wed 6:00 Wyner-Ziv Estimators: Efficient Distributed Mean Estimation with Side-Information
Prathamesh Mayekar, Ananda Theertha Suresh, Himanshu Tyagi
Poster
Wed 6:00 Causal Autoregressive Flows
Ilyes Khemakhem, Ricardo Monti, Robert Leech, Aapo Hyvarinen
Poster
Wed 6:00 Fisher Auto-Encoders
Khalil Elkhalil, Ali Hasan, Jie Ding, Sina Farsiu, Vahid Tarokh
Poster
Wed 6:00 Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
Qiming Du, Gérard Biau, Francois Petit, Raphaël Porcher
Poster
Wed 6:00 Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond
Nina Vesseron, Ievgen Redko, Charlotte Laclau
Poster
Wed 6:00 All of the Fairness for Edge Prediction with Optimal Transport
Charlotte Laclau, Ievgen Redko, Manvi Choudhary, Christine Largeron
Poster
Wed 6:00 The Sample Complexity of Level Set Approximation
Francois Bachoc, Tom Cesari, Sébastien Gerchinovitz
Poster
Wed 6:00 Sparse Gaussian Processes Revisited: Bayesian Approaches to Inducing-Variable Approximations
Simone Rossi, Markus Heinonen, Edwin Bonilla, Zheyang Shen, Maurizio Filippone
Poster
Wed 6:00 Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Poster
Wed 6:00 On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions
Kai Brügge, Asja Fischer, Christian Igel
Poster
Wed 6:00 Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Vikas Garg, Adam Tauman Kalai, Katrina Ligett, Steven Wu
Poster
Wed 6:00 Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization
Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
Poster
Wed 6:00 Sequential Random Sampling Revisited: Hidden Shuffle Method
Michael Shekelyan, Graham Cormode
Poster
Wed 6:00 CONTRA: Contrarian statistics for controlled variable selection
Mukund Sudarshan, Aahlad Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath
Poster
Wed 6:00 Nearest Neighbour Based Estimates of Gradients: Sharp Nonasymptotic Bounds and Applications
Guillaume Ausset, Stephan Clémençon, François Portier
Poster
Wed 6:00 Foundations of Bayesian Learning from Synthetic Data
Harrison Wilde, Jack Jewson, Sebastian Vollmer, Chris Holmes
Poster
Wed 6:00 Learning Bijective Feature Maps for Linear ICA
Alexander Camuto, Matthew Willetts, Chris Holmes, Brooks Paige, Stephen Roberts
Poster
Wed 6:00 Budgeted and Non-Budgeted Causal Bandits
Vineet Nair, Vishakha Patil, Gaurav Sinha
Poster
Wed 6:00 On the Memory Mechanism of Tensor-Power Recurrent Models
Hejia Qiu, Chao Li, Ying Weng, Zhun Sun, Xingyu He, Qibin Zhao
Poster
Wed 6:00 Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry
Qadeer Khan, Patrick Wenzel, Daniel Cremers
Poster
Wed 6:00 Quantum Tensor Networks, Stochastic Processes, and Weighted Automata
Sandesh Adhikary, Siddarth Srinivasan, Jacob E Miller, Guillaume Rabusseau, Byron Boots
Poster
Wed 6:00 Kernel regression in high dimensions: Refined analysis beyond double descent
Fanghui Liu, Zhenyu Liao, Johan Suykens
Poster
Wed 6:00 Logical Team Q-learning: An approach towards factored policies in cooperative MARL
Lucas Cassano, Ali H. Sayed
Poster
Wed 6:00 Neural Enhanced Belief Propagation on Factor Graphs
Víctor Garcia Satorras, Max Welling
Poster
Wed 6:00 Predictive Complexity Priors
Eric Nalisnick, Jonathan Gordon, Jose Miguel Hernandez-Lobato
Poster
Wed 6:00 Improving predictions of Bayesian neural nets via local linearization
Alex Immer, Maciej Korzepa, Matthias Bauer
Poster
Wed 6:00 Differentiable Divergences Between Time Series
Mathieu Blondel, Arthur Mensch, Jean-Philippe Vert
Poster
Wed 6:00 Differentiating the Value Function by using Convex Duality
Sheheryar Mehmood, Peter Ochs
Poster
Wed 6:00 Nested Barycentric Coordinate System as an Explicit Feature Map
Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele
Poster
Wed 6:00 Deep Fourier Kernel for Self-Attentive Point Processes
Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie
Poster
Wed 6:00 Interpretable Random Forests via Rule Extraction
Clément Bénard, Gérard Biau, Sébastien da Veiga, Erwan Scornet
Poster
Wed 6:00 Improved Exploration in Factored Average-Reward MDPs
Mohammad Sadegh Talebi, Anders Jonsson, Odalric Maillard
Poster
Wed 6:00 Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy
Onur Teymur, Jackson Gorham, Marina Riabiz, Chris Oates
Poster
Wed 6:00 Linearly Constrained Gaussian Processes with Boundary Conditions
Markus Lange-Hegermann
Poster
Wed 6:00 Latent Derivative Bayesian Last Layer Networks
Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters
Poster
Wed 6:00 Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
Yahav Bechavod, Katrina Ligett, Steven Wu, Juba Ziani
Poster
Wed 6:00 Anderson acceleration of coordinate descent
Quentin Bertrand, Mathurin Massias
Poster
Wed 6:00 Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence
Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien
Poster
Wed 6:00 SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
Robert Gower, Othmane Sebbouh, Nicolas Loizou
Poster
Wed 6:00 Hyperparameter Transfer Learning with Adaptive Complexity
Samuel Horváth, Aaron Klein, Peter Richtarik, Cedric Archambeau
Poster
Wed 6:00 Online probabilistic label trees
Marek Wydmuch, Kalina Jasinska-Kobus, Devanathan Thiruvenkatachari, Krzysztof Dembczynski
Poster
Wed 6:00 Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth, Mihaela van der Schaar
Poster
Wed 6:00 Offline detection of change-points in the mean for stationary graph signals.
Alejandro de la Concha Duarte, Nicolas Vayatis, Argyris Kalogeratos
Poster
Wed 6:00 Robust and Private Learning of Halfspaces
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen
Poster
Wed 6:00 On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models
Yuyang Shi, Rob Cornish
Poster
Wed 6:00 On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning
Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
Poster Session
Wed 6:00 Poster Session 3
Poster
Wed 6:00 On the number of linear functions composing deep neural network: Towards a refined definition of neural networks complexity
Yuuki Takai, Akiyoshi Sannai, Matthieu Cordonnier
Poster
Wed 6:00 Logistic Q-Learning
Joan Bas Serrano, Sebastian Curi, Andreas Krause, Gergely Neu
Poster
Wed 6:00 Equitable and Optimal Transport with Multiple Agents
Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi
Poster
Wed 6:00 Local Competition and Stochasticity for Adversarial Robustness in Deep Learning
Konstantinos Panagiotis Panousis, Sotirios Chatzis, Antonios Alexos, Sergios Theodoridis
Poster
Wed 6:00 Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints
Robin Vogel, Aurélien Bellet, Stephan Clémençon
Poster
Wed 6:00 Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
Lisa Schut, Oscar Key, Rory Mc Grath, Luca Costabello, Bogdan Sacaleanu, medb corcoran, Yarin Gal
Poster
Wed 6:00 High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard
Poster
Wed 6:00 Free-rider Attacks on Model Aggregation in Federated Learning
Yann Fraboni, Richard Vidal, Marco Lorenzi
Poster
Wed 6:00 DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation
Frederik Harder, Kamil Adamczewski, Mijung Park
Poster
Wed 6:00 Aggregating Incomplete and Noisy Rankings
Dimitris Fotakis, Alkis Kalavasis, Kostas Stavropoulos
Poster
Wed 6:00 On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
Alain Durmus, Pablo Jiménez, Eric Moulines, Salem SAID
Poster
Wed 6:00 Couplings for Multinomial Hamiltonian Monte Carlo
Kai Xu, Tor Erlend Fjelde, Charles Sutton, Hong Ge
Poster
Wed 6:00 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
Tianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng
Poster
Wed 6:00 Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes
Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, xiao wang
Poster
Wed 6:00 A Variational Inference Approach to Learning Multivariate Wold Processes
Jalal Etesami, William Trouleau, Negar Kiyavash, Matthias Grossglauser, Patrick Thiran
Poster
Wed 6:00 ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frederic Chazal, Clément Levrard, Yuhei Umeda, Yuichi Ike
Poster
Wed 6:00 Inference in Stochastic Epidemic Models via Multinomial Approximations
Nick Whiteley, Lorenzo Rimella
Poster
Wed 6:00 Amortized Bayesian Prototype Meta-learning: A New Probabilistic Meta-learning Approach to Few-shot Image Classification
Zhuo Sun, Jijie Wu, Xiaoxu Li, Wenming Yang, Jing-Hao Xue
Poster
Wed 6:00 SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
Hyun-Suk Lee, Cong Shen, William Zame, Jang-Won Lee, Mihaela van der Schaar
Poster
Wed 6:00 Efficient Statistics for Sparse Graphical Models from Truncated Samples
Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan, Ioannis Panageas
Poster
Wed 6:00 An Analysis of the Adaptation Speed of Causal Models
Remi Le Priol, Reza Babanezhad, Yoshua Bengio, Simon Lacoste-Julien
Poster
Wed 6:00 A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtarik, Sebastian Stich
Poster
Wed 6:00 Improved Complexity Bounds in Wasserstein Barycenter Problem
Darina Dvinskikh, Daniil Tiapkin
Poster
Wed 6:00 Adaptive Sampling for Fast Constrained Maximization of Submodular Functions
Francesco Quinzan, Vanja Doskoc, Andreas Göbel, Tobias Friedrich
Poster
Wed 6:00 Dirichlet Pruning for Convolutional Neural Networks
Kamil Adamczewski, Mijung Park
Poster
Wed 6:00 Deep Generative Missingness Pattern-Set Mixture Models
Sahra Ghalebikesabi, Rob Cornish, Chris Holmes, Luke Kelly
Poster
Wed 6:00 Direct-Search for a Class of Stochastic Min-Max Problems
Sotiris Anagnostidis, Aurelien Lucchi, Youssef Diouane
Poster
Wed 6:00 A Theoretical Characterization of Semi-supervised Learning with Self-training for Gaussian Mixture Models
Samet Oymak, Talha Cihad Gulcu
Poster
Wed 6:00 Adaptive wavelet pooling for convolutional neural networks
Moritz Wolter, Jochen Garcke
Poster
Wed 6:00 Multi-Armed Bandits with Cost Subsidy
Deeksha Sinha, Karthik Abinav Sankararaman, Abbas Kazerouni, Vashist Avadhanula
Poster
Wed 6:00 Online k-means Clustering
Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom
Poster
Wed 6:00 Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning
Kai Cui, Heinz Koeppl
Poster
Wed 6:00 Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures
Fanghui Liu, Xiaolin Huang, Yingyi Chen, Johan Suykens
Poster
Wed 6:00 Scalable Gaussian Process Variational Autoencoders
Metod Jazbec, Matt Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch
Poster
Wed 6:00 A unified view of likelihood ratio and reparameterization gradients
Paavo Parmas, Masashi Sugiyama
Poster
Wed 6:00 Learning Complexity of Simulated Annealing
Avrim Blum, Chen Dan, Saeed Seddighin
Oral Session
Wed 8:15 Theory and Methods of Learning
Oral
Wed 8:15 Neural Enhanced Belief Propagation on Factor Graphs
Víctor Garcia Satorras, Max Welling
Oral
Wed 8:30 An Analysis of LIME for Text Data
Dina Mardaoui, Damien Garreau
Oral
Wed 8:45 Bandit algorithms: Letting go of logarithmic regret for statistical robustness
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha, Krishna Jagannathan
Oral
Wed 9:00 The Sample Complexity of Level Set Approximation
Francois Bachoc, Tom Cesari, Sébastien Gerchinovitz
Oral Session
Wed 9:15 Bandits, Reinforcement Learning / Learning Theory / Sparse Methods
Oral
Wed 9:15 Logistic Q-Learning
Joan Bas Serrano, Sebastian Curi, Andreas Krause, Gergely Neu
Oral
Wed 9:30 Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille, Louis Faury, Clement Calauzenes
Oral
Wed 9:45 Robust and Private Learning of Halfspaces
Badih Ghazi, Ravi Kumar, Pasin Manurangsi, Thao Nguyen
Oral
Wed 10:00 Hadamard Wirtinger Flow for Sparse Phase Retrieval
Fan Wu, Patrick Rebeschini
Oral
Wed 10:30 Projection-Free Optimization on Uniformly Convex Sets
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Oral Session
Wed 10:30 Optimization / Learning Theory / Generalization
Oral
Wed 10:45 Measure Transport with Kernel Stein Discrepancy
Matthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris Oates
Oral
Wed 11:00 Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Vikas Garg, Adam Tauman Kalai, Katrina Ligett, Steven Wu
Oral
Wed 11:15 Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
Oral
Wed 11:30 Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
Nafiseh Ghoroghchian, Gautam Dasarathy, Stark Draper
Oral Session
Wed 11:30 Graphs and Networks
Oral
Wed 11:45 Matérn Gaussian Processes on Graphs
Slava Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Deisenroth, Nicolas Durrande
Oral
Wed 12:00 Differentially Private Analysis on Graph Streams
Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora
Oral
Wed 12:15 On Learning Continuous Pairwise Markov Random Fields
Abhin Shah, Devavrat Shah, Gregory Wornell
Poster
Wed 12:45 Direct Loss Minimization for Sparse Gaussian Processes
Yadi Wei, Rishit Sheth, Roni Khardon
Poster
Wed 12:45 Hierarchical Clustering in General Metric Spaces using Approximate Nearest Neighbors
Benjamin Moseley, Sergei Vassilvtiskii, Yuyan Wang
Poster
Wed 12:45 Fair for All: Best-effort Fairness Guarantees for Classification
Anilesh K. Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala
Poster
Wed 12:45 Efficient Designs Of SLOPE Penalty Sequences In Finite Dimension
Yiliang Zhang, Zhiqi Bu
Poster
Wed 12:45 Power of Hints for Online Learning with Movement Costs
Aditya Bhaskara, Ashok Cutkosky, Ravi Kumar, Manish Purohit
Poster
Wed 12:45 Location Trace Privacy Under Conditional Priors
Casey Meehan, Kamalika Chaudhuri
Poster
Wed 12:45 The Multiple Instance Learning Gaussian Process Probit Model
Fulton Wang, Ali Pinar
Poster
Wed 12:45 Finite-Sample Regret Bound for Distributionally Robust Offline Tabular Reinforcement Learning
Zhengqing Zhou, Qinxun Bai, Zhengyuan Zhou, Linhai Qiu, Jose Blanchet, Peter Glynn
Poster
Wed 12:45 Differentially Private Analysis on Graph Streams
Jalaj Upadhyay, Sarvagya Upadhyay, Raman Arora
Poster
Wed 12:45 Regret-Optimal Filtering
Oron Sabag, Babak Hassibi
Poster
Wed 12:45 Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation
Yuki Ohnishi, Jean Honorio
Poster
Wed 12:45 Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
Poster
Wed 12:45 A Statistical Perspective on Coreset Density Estimation
Paxton Turner, Jingbo Liu, Philippe Rigollet
Poster
Wed 12:45 CLAR: Contrastive Learning of Auditory Representations
Haider Al-Tahan, Yalda Mohsenzadeh
Poster
Wed 12:45 Fast and Smooth Interpolation on Wasserstein Space
Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin Stromme
Poster
Wed 12:45 Geometrically Enriched Latent Spaces
Georgios Arvanitidis, Soren Hauberg, Bernhard Schölkopf
Poster
Wed 12:45 Approximation Algorithms for Orthogonal Non-negative Matrix Factorization
Moses Charikar, Lunjia Hu
Poster
Wed 12:45 Abstract Value Iteration for Hierarchical Reinforcement Learning
Kishor Jothimurugan, Osbert Bastani, Rajeev Alur
Poster
Wed 12:45 Hyperbolic graph embedding with enhanced semi-implicit variational inference.
Ali Lotfi Rezaabad, Rahi Kalantari, Sriram Vishwanath, Mingyuan Zhou, Jonathan Tamir
Poster
Wed 12:45 Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari, Mehrdad Mahdavi
Poster
Wed 12:45 Private optimization without constraint violations
andres munoz, Umar Syed, Sergei Vassilvtiskii, Ellen Vitercik
Poster
Wed 12:45 On the Consistency of Metric and Non-Metric K-Medoids
He Jiang, Ery Arias-Castro
Poster
Wed 12:45 Faster & More Reliable Tuning of Neural Networks: Bayesian Optimization with Importance Sampling
Setareh Ariafar, Zelda Mariet, Dana Brooks, Jennifer Dy, Jasper Snoek
Poster
Wed 12:45 Kernel Interpolation for Scalable Online Gaussian Processes
Sam Stanton, Wesley Maddox, Ian Delbridge, Andrew Gordon Wilson
Poster
Wed 12:45 Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation
Chen-Yu Wei, Mehdi Jafarnia, Haipeng Luo, Rahul Jain
Poster
Wed 12:45 Robust hypothesis testing and distribution estimation in Hellinger distance
Ananda Theertha Suresh
Poster
Wed 12:45 Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers
Lunjia Hu, Omer Reingold
Poster
Wed 12:45 Exploiting Equality Constraints in Causal Inference
Chi Zhang, Carlos Cinelli, Bryant Chen, Judea Pearl
Poster
Wed 12:45 Rate-Regularization and Generalization in Variational Autoencoders
Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana Brooks, Jennifer Dy, Jan-Willem van de Meent
Poster
Wed 12:45 Learning Smooth and Fair Representations
Xavier Gitiaux, Huzefa Rangwala
Poster
Wed 12:45 A Variational Information Bottleneck Approach to Multi-Omics Data Integration
Changhee Lee, Mihaela van der Schaar
Poster
Wed 12:45 When MAML Can Adapt Fast and How to Assist When It Cannot
Séb Arnold, Shariq Iqbal, Fei Sha
Poster
Wed 12:45 Evaluating Model Robustness and Stability to Dataset Shift
Adarsh Subbaswamy, Roy Adams, Suchi Saria
Poster
Wed 12:45 Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
Maxime Vandegar, Michael Kagan, Antoine Wehenkel, Gilles Louppe
Poster
Wed 12:45 False Discovery Rates in Biological Networks
Lu Yu, Tobias Kaufmann, Johannes Lederer
Poster
Wed 12:45 Efficient Balanced Treatment Assignments for Experimentation
David Arbour, Drew Dimmery, Anup Rao
Poster
Wed 12:45 Probabilistic Sequential Matrix Factorization
Omer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas, Mark Steel
Poster
Wed 12:45 A Fast and Robust Method for Global Topological Functional Optimization
Elchanan Solomon, Alexander Wagner, Paul Bendich
Poster
Wed 12:45 A Change of Variables Method For Rectangular Matrix-Vector Products
Edmond Cunningham, Madalina Fiterau
Poster
Wed 12:45 Low-Rank Generalized Linear Bandit Problems
Yangyi Lu, Amirhossein Meisami, Ambuj Tewari
Poster
Wed 12:45 A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach
Poster
Wed 12:45 Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency
yuyang deng, Mehrdad Mahdavi
Poster
Wed 12:45 A Deterministic Streaming Sketch for Ridge Regression
Benwei Shi, Jeff Phillips
Poster
Wed 12:45 Feedback Coding for Active Learning
Greg Canal, Matthieu Bloch, Christopher Rozell
Poster
Wed 12:45 Principal Component Regression with Semirandom Observations via Matrix Completion
Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Pruthuvi Maheshakya Wijewardena
Poster
Wed 12:45 Understanding Robustness in Teacher-Student Setting: A New Perspective
Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian
Poster
Wed 12:45 One-Sketch-for-All: Non-linear Random Features from Compressed Linear Measurements
Xiaoyun Li, Ping Li
Poster
Wed 12:45 Evading the Curse of Dimensionality in Unconstrained Private GLMs
Shuang Song, Thomas Steinke, Om Thakkar, Abhradeep Thakurta
Poster
Wed 12:45 Automatic Differentiation Variational Inference with Mixtures
Warren Morningstar, Sharad Vikram, Cusuh Ham, Andrew Gallagher, Joshua Dillon
Poster
Wed 12:45 Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
Nikhil Mehta, Kevin Liang, Vinay Kumar Verma, Lawrence Carin Duke
Poster
Wed 12:45 A Theory of Multiple-Source Adaptation with Limited Target Labeled Data
Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu
Poster
Wed 12:45 Provably Safe PAC-MDP Exploration Using Analogies
Melrose Roderick, Vaishnavh Nagarajan, Zico Kolter
Poster
Wed 12:45 On Data Efficiency of Meta-learning
Maruan Al-Shedivat, Liam Li, Eric Xing, Ameet Talwalkar
Poster Session
Wed 12:45 Poster Session 4
Poster
Wed 12:45 Scalable Constrained Bayesian Optimization
David Eriksson, Matthias Poloczek
Poster
Wed 12:45 Deep Probabilistic Accelerated Evaluation: A Robust Certifiable Rare-Event Simulation Methodology for Black-Box Safety-Critical Systems
Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, Ding Zhao
Poster
Wed 12:45 Meta-Learning Divergences for Variational Inference
Ruqi Zhang, Yingzhen Li, Christopher De Sa, Sam Devlin, Cheng Zhang
Poster
Wed 12:45 Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression
Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan Tibshirani
Poster
Wed 12:45 Decision Making Problems with Funnel Structure: A Multi-Task Learning Approach with Application to Email Marketing Campaigns
Ziping Xu, Amirhossein Meisami, Ambuj Tewari
Poster
Wed 12:45 Towards Flexible Device Participation in Federated Learning
Yichen Ruan, Xiaoxi Zhang, Shu-Che Liang, Carlee Joe-Wong
Poster
Wed 12:45 Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries
Steve Hanneke, Liu Yang
Poster
Wed 12:45 Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization
Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu
Poster
Wed 12:45 DebiNet: Debiasing Linear Models with Nonlinear Overparameterized Neural Networks
Shiyun Xu, Zhiqi Bu
Poster
Wed 12:45 Stability and Differential Privacy of Stochastic Gradient Descent for Pairwise Learning with Non-Smooth Loss
Zhenhuan Yang, Yunwen Lei, Siwei Lyu, Yiming Ying
Poster
Wed 12:45 On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression
Jeongyeol Kwon, Nhat Ho, Constantine Caramanis
Poster
Wed 12:45 Selective Classification via One-Sided Prediction
Aditya Gangrade, Anil Kag, Venkatesh Saligrama
Poster
Wed 12:45 Contextual Blocking Bandits
Soumya Basu, Orestis Papadigenopoulos, Constantine Caramanis, Sanjay Shakkottai
Poster
Wed 12:45 Curriculum Learning by Optimizing Learning Dynamics
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
Poster
Wed 12:45 Combinatorial Gaussian Process Bandits with Probabilistically Triggered Arms
Ilker Demirel, Cem Tekin
Poster
Wed 12:45 Significance of Gradient Information in Bayesian Optimization
Shubhanshu Shekhar, Tara Javidi
Poster
Wed 12:45 Shuffled Model of Differential Privacy in Federated Learning
Antonious Girgis, Deepesh Data, Suhas Diggavi, Peter Kairouz, Ananda Theertha Suresh
Poster
Wed 12:45 Provable Hierarchical Imitation Learning via EM
Zhiyu Zhang, Yannis Paschalidis
Poster
Wed 12:45 Hidden Cost of Randomized Smoothing
Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
Poster
Wed 12:45 Learning Prediction Intervals for Regression: Generalization and Calibration
Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang
Poster
Wed 12:45 Product Manifold Learning
Sharon Zhang, Amit Moscovich, Amit Singer
Poster
Wed 12:45 Localizing Changes in High-Dimensional Regression Models
Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, Yi Yu
Poster
Wed 12:45 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions
Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Günnemann
Poster
Wed 12:45 Reaping the Benefits of Bundling under High Production Costs
Will Ma, David Simchi-Levi
Poster
Wed 12:45 Learning to Defend by Learning to Attack
Haoming Jiang, Zhehui Chen, Yuyang Shi, Bo Dai, Tuo Zhao
Poster
Wed 12:45 Goodness-of-Fit Test for Mismatched Self-Exciting Processes
Song Wei, Shixiang Zhu, Minghe Zhang, Yao Xie
Poster
Wed 12:45 Improving KernelSHAP: Practical Shapley Value Estimation Using Linear Regression
Ian Covert, Su-In Lee
Poster
Wed 12:45 Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
Nathaniel Grammel, Brian Brubach, Will Ma, Aravind Srinivasan
Poster
Wed 12:45 Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear Time
Alan Kuhnle
Poster
Wed 12:45 A Study of Condition Numbers for First-Order Optimization
Charles Guille-Escuret, Manuela Girotti, Baptiste Goujaud, Ioannis Mitliagkas
Poster
Wed 12:45 Large Scale K-Median Clustering for Stable Clustering Instances
Konstantin Voevodski
Poster
Wed 12:45 Stochastic Bandits with Linear Constraints
Aldo Pacchiano, Mohammad Ghavamzadeh, Peter Bartlett, Heinrich Jiang
Poster
Wed 12:45 Rao-Blackwellised parallel MCMC
Tobias Schwedes, Ben Calderhead
Poster
Wed 12:45 Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms
Yilun Zhou, Adithya Renduchintala, Xian Li, Sida Wang, Yashar Mehdad, Asish Ghoshal
Poster
Wed 12:45 Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi
Mentorship
Wed 15:00 Mentorship Session 4
Invited Talk
Wed 16:00 Veridical Data Science: The Practice of Responsible Data Analysis and Decision-Making
Bin Yu
Affinity Event
Wed 17:15 Caucus for Women in Statistics
Wendy Lou
Mentorship
Wed 17:30 Mentorship Session 5
Mentorship
Thu 4:00 Mentorship Session 6
Invited Talk
Thu 6:00 Recent Progress in Simulation-Based Inference
Kyle Cranmer
Poster
Thu 7:30 High-Dimensional Feature Selection for Sample Efficient Treatment Effect Estimation
Kristjan Greenewald, Karthikeyan Shanmugam, Dmitriy Katz
Poster
Thu 7:30 The Teaching Dimension of Kernel Perceptron
Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen
Poster
Thu 7:30 LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads
Hossein Shokri Ghadikolaei, Sebastian Stich, Martin Jaggi
Poster
Thu 7:30 Clustering multilayer graphs with missing nodes
Guillaume Braun, Hemant Tyagi, Christophe Biernacki
Poster
Thu 7:30 Fractional moment-preserving initialization schemes for training deep neural networks
Mert Gurbuzbalaban, Yuanhan Hu
Poster
Thu 7:30 An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo
Matthew Hoffman, Alexey Radul, Pavel Sountsov
Poster
Thu 7:30 Noise Contrastive Meta-Learning for ConditionalDensity Estimation using Kernel Mean Embeddings
Jean-Francois Ton, Lucian CHAN, Yee Whye Teh, Dino Sejdinovic
Poster
Thu 7:30 Transforming Gaussian Processes With Normalizing Flows
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas
Poster
Thu 7:30 Stochastic Linear Bandits Robust to Adversarial Attacks
Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett
Poster
Thu 7:30 Hadamard Wirtinger Flow for Sparse Phase Retrieval
Fan Wu, Patrick Rebeschini
Poster
Thu 7:30 Variational Autoencoder with Learned Latent Structure
Marissa Connor, Greg Canal, Christopher Rozell
Poster
Thu 7:30 A Spectral Analysis of Dot-product Kernels
Meyer Scetbon, Zaid Harchaoui
Poster
Thu 7:30 On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili, Kia Khezeli, Victor Picheny
Poster
Thu 7:30 Model updating after interventions paradoxically introduces bias
James Liley, Sam Emerson, Bilal Mateen, Catalina Vallejos, Louis Aslett, Sebastian Vollmer
Poster
Thu 7:30 Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
Leena Chennuru Vankadara, Sebastian Bordt, Ulrike von Luxburg, Debarghya Ghoshdastidar
Poster
Thu 7:30 Robust Learning under Strong Noise via SQs
Ioannis Anagnostides, Themis Gouleakis, Ali Marashian
Poster
Thu 7:30 Efficient Computation and Analysis of Distributional Shapley Values
Yongchan Kwon, Manuel A. Rivas, James Zou
Poster
Thu 7:30 When OT meets MoM: Robust estimation of Wasserstein Distance
Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d'Alché-Buc
Poster
Thu 7:30 Generalized Spectral Clustering via Gromov-Wasserstein Learning
Samir Chowdhury, Tom Needham
Poster
Thu 7:30 Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models
Sasi Kumar Murakonda, Reza Shokri, George Theodorakopoulos
Poster
Thu 7:30 Federated f-Differential Privacy
Qinqing Zheng, Shuxiao Chen, Qi Long, Weijie Su
Poster
Thu 7:30 Convergence Properties of Stochastic Hypergradients
Riccardo Grazzi, Massimiliano Pontil, Saverio Salzo
Poster
Thu 7:30 Automatic structured variational inference
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven
Poster
Thu 7:30 Smooth Bandit Optimization: Generalization to Holder Space
Yusha Liu, Yining Wang, Aarti Singh
Poster
Thu 7:30 The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers
Mohamed El Amine Seddik, Cosme Louart, Romain COUILLET, Mohamed Tamaazousti
Poster
Thu 7:30 Aligning Time Series on Incomparable Spaces
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Deisenroth
Poster
Thu 7:30 Learning Contact Dynamics using Physically Structured Neural Networks
Andreas Hochlehnert, Alexander Terenin, Steindor Saemundsson, Marc Deisenroth
Poster
Thu 7:30 Self-Concordant Analysis of Generalized Linear Bandits with Forgetting
Yoan Russac, Louis Faury, Olivier Cappé, Aurélien Garivier
Poster
Thu 7:30 CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices
Valerii Likhosherstov, Jared Davis, Krzysztof Choromanski, Adrian Weller
Poster
Thu 7:30 Approximate Message Passing with Spectral Initialization for Generalized Linear Models
Marco Mondelli, Ramji Venkataramanan
Poster
Thu 7:30 Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
Ilja Kuzborskij , Claire Vernade, Andras Gyorgy, Csaba Szepesvari
Poster
Thu 7:30 Stochastic Gradient Descent Meets Distribution Regression
Nicole Mücke
Poster
Thu 7:30 Active Learning with Maximum Margin Sparse Gaussian Processes
Weishi Shi, Qi Yu
Poster
Thu 7:30 Learning Matching Representations for Individualized Organ Transplantation Allocation
Can Xu, Ahmed Alaa, Ioana Bica, Brent Ershoff, Maxime Cannesson, Mihaela van der Schaar
Session
Thu 7:30 Oral Session 9
Poster
Thu 7:30 Projection-Free Optimization on Uniformly Convex Sets
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
Poster
Thu 7:30 Context-Specific Likelihood Weighting
Nitesh Kumar, Ondřej Kuželka
Poster
Thu 7:30 On the role of data in PAC-Bayes
Gintare Karolina Dziugaite, Kyle Hsu, Waseem Gharbieh, Gabriel Arpino, Daniel Roy
Poster
Thu 7:30 A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models
Jiaxin Zhang, Sirui Bi, Guannan Zhang
Poster
Thu 7:30 Causal Inference under Networked Interference and Intervention Policy Enhancement
Yunpu Ma, Volker Tresp
Poster
Thu 7:30 Hierarchical Clustering via Sketches and Hierarchical Correlation Clustering
Danny Vainstein, Vaggos Chatziafratis, Gui Citovsky, Anand Rajagopalan, Mohammad Mahdian, Yossi Azar
Poster
Thu 7:30 Understanding and Mitigating Exploding Inverses in Invertible Neural Networks
Jens Behrmann, Paul Vicol, Kuan-Chieh Wang, Roger Grosse, Joern-Henrik Jacobsen
Poster
Thu 7:30 Moment-Based Variational Inference for Stochastic Differential Equations
Christian Wildner, Heinz Koeppl
Poster
Thu 7:30 Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent
Suriya Gunasekar, Blake Woodworth, Nathan Srebro
Poster
Thu 7:30 Continuum-Armed Bandits: A Function Space Perspective
Shashank Singh
Poster
Thu 7:30 Approximate Data Deletion from Machine Learning Models
Zachary Izzo, Mary Anne Smart, Kamalika Chaudhuri, James Zou
Poster
Thu 7:30 Learning User Preferences in Non-Stationary Environments
Wasim Huleihel, Soumyabrata Pal, Ofer Shayevitz
Poster
Thu 7:30 Distribution Regression for Sequential Data
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin Bonilla, Terry Lyons
Poster
Thu 7:30 Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, Wipf David
Poster
Thu 7:30 Optimizing Percentile Criterion using Robust MDPs
Bahram Behzadian, Reazul Hasan Russel, Marek Petrik, Chin Pang Ho
Poster
Thu 7:30 Measure Transport with Kernel Stein Discrepancy
Matthew Fisher, Tui Nolan, Matthew Graham, Dennis Prangle, Chris Oates
Poster
Thu 7:30 Adaptive Approximate Policy Iteration
Botao Hao, Nevena Lazic, Yasin Abbasi-Yadkori, Pooria Joulani, Csaba Szepesvari
Poster
Thu 7:30 Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
Manuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir
Poster
Thu 7:30 Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
Nafiseh Ghoroghchian, Gautam Dasarathy, Stark Draper
Poster
Thu 7:30 Revisiting Projection-free Online Learning: the Strongly Convex Case
Ben Kretzu, Dan Garber
Poster
Thu 7:30 Explicit Regularization of Stochastic Gradient Methods through Duality
Anant Raj, Francis Bach
Poster
Thu 7:30 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth
Poster
Thu 7:30 Reinforcement Learning in Parametric MDPs with Exponential Families
Sayak Ray Chowdhury, Aditya Gopalan, Odalric Maillard
Poster
Thu 7:30 When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence
Ziwei Guan, Tengyu Xu, Yingbin Liang
Poster Session
Thu 7:30 Poster Session 5
Poster
Thu 7:30 No-regret Algorithms for Multi-task Bayesian Optimization
Sayak Ray Chowdhury, Aditya Gopalan
Poster
Thu 7:30 LassoNet: Neural Networks with Feature Sparsity
Ismael Lemhadri, Feng Ruan, Rob Tibshirani
Poster
Thu 7:30 Approximating Lipschitz continuous functions with GroupSort neural networks
Ugo Tanielian, Gerard Biau
Poster
Thu 7:30 Local SGD: Unified Theory and New Efficient Methods
Eduard Gorbunov, Filip Hanzely, Peter Richtarik
Poster
Thu 7:30 A Stein Goodness-of-test for Exponential Random Graph Models
Wenkai Xu, Gesine Reinert
Poster
Thu 7:30 Sparse Algorithms for Markovian Gaussian Processes
William Wilkinson, Arno Solin, Vincent Adam
Poster
Thu 7:30 Latent Gaussian process with composite likelihoods and numerical quadrature
Siddharth Ramchandran, Miika Koskinen, Harri Lähdesmäki
Poster
Thu 7:30 Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger, Zhiwu Huang, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool
Poster
Thu 7:30 Reinforcement Learning for Constrained Markov Decision Processes
Ather Gattami, Qinbo Bai, Vaneet Aggarwal
Poster
Thu 7:30 Asymptotics of Ridge(less) Regression under General Source Condition
Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco
Poster
Thu 7:30 Faster Kernel Interpolation for Gaussian Processes
Mohit Yadav, Daniel Sheldon, Cameron Musco
Poster
Thu 7:30 Iterative regularization for convex regularizers
Cesare Molinari, Mathurin Massias, Lorenzo Rosasco, Silvia Villa
Poster
Thu 7:30 A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces
Omar Darwiche Domingues, Pierre Menard, Matteo Pirotta, Emilie Kaufmann, Michal Valko
Poster
Thu 7:30 A Contraction Approach to Model-based Reinforcement Learning
Ting-Han Fan, Peter Ramadge
Poster
Thu 7:30 Online Sparse Reinforcement Learning
Botao Hao, Tor Lattimore, Csaba Szepesvari, Mengdi Wang
Poster
Thu 7:30 Online Active Model Selection for Pre-trained Classifiers
Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš, Johannes Rausch, Ce Zhang, Andreas Krause
Poster
Thu 7:30 Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models
Jan Achterhold, Joerg Stueckler
Poster
Thu 7:30 Benchmarking Simulation-Based Inference
Jan-Matthis Lueckmann, Jan Boelts, David Greenberg, Pedro Goncalves, Jakob Macke
Poster
Thu 7:30 Why did the distribution change?
Kailash Budhathoki, Dominik Janzing, Patrick Bloebaum, Hoiyi Ng
Poster
Thu 7:30 Bayesian Inference with Certifiable Adversarial Robustness
Matthew Wicker, Luca Laurenti, Andrea Patane, Zhuotong Chen, Zheng Zhang, Marta Kwiatkowska
Poster
Thu 7:30 Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
Sebastian Stich, Amirkeivan Mohtashami, Martin Jaggi
Poster
Thu 7:30 Longitudinal Variational Autoencoder
Siddharth Ramchandran, Gleb Tikhonov, Kalle Kujanpää, Miika Koskinen, Harri Lähdesmäki
Poster
Thu 7:30 Fourier Bases for Solving Permutation Puzzles
Horace Pan, Risi Kondor
Poster
Thu 7:30 Group testing for connected communities
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas Diggavi
Poster
Thu 7:30 Variational inference for nonlinear ordinary differential equations
Sanmitra Ghosh, Paul Birrell, Daniela De Angelis
Poster
Thu 7:30 Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
Poster
Thu 7:30 Momentum Improves Optimization on Riemannian Manifolds
Foivos Alimisis, Antonio Orvieto, Gary Becigneul, Aurelien Lucchi
Poster
Thu 7:30 Latent variable modeling with random features
Gregory Gundersen, Michael Zhang, Barbara Engelhardt
Poster
Thu 7:30 Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
Marc Abeille, Louis Faury, Clement Calauzenes
Poster
Thu 7:30 Stable ResNet
Soufiane Hayou, Eugenio Clerico, Bobby He, George Deligiannidis, Arnaud Doucet, Judith Rousseau
Poster
Thu 7:30 Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
Jeremiah Liu
Poster
Thu 7:30 Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT
Antti Koskela, Joonas Jälkö, Lukas Prediger, Antti Honkela
Poster
Thu 7:30 Learning with Hyperspherical Uniformity
Weiyang Liu, Rongmei Lin, Zhen Liu, Li Xiong, Bernhard Schölkopf, Adrian Weller
Session
Thu 8:30 Oral Session 10
Mentorship
Thu 9:45 Mentorship Session 7
Oral Session
Thu 12:00 Fairness / Privacy / Decision Making / Data Cleaning
Oral
Thu 12:00 Private optimization without constraint violations
andres munoz, Umar Syed, Sergei Vassilvtiskii, Ellen Vitercik
Oral
Thu 12:15 Learning Smooth and Fair Representations
Xavier Gitiaux, Huzefa Rangwala
Oral
Thu 12:30 Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration
Shengjia Zhao, Stefano Ermon
Oral
Thu 12:45 PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming
Alexander Lew, Monica Agrawal, David Sontag, Vikash Mansinghka
Oral Session
Thu 13:00 Generalization / Reinforcement Learning / Optimization
Oral
Thu 13:00 Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders
Andrew Bennett, Nathan Kallus, Lihong Li, Ali Mousavi
Oral
Thu 13:15 Does Invariant Risk Minimization Capture Invariance?
Pritish Kamath, Akilesh Tangella, Danica Sutherland, Nathan Srebro
Oral
Thu 13:30 Density of States Estimation for Out of Distribution Detection
Warren Morningstar, Cusuh Ham, Andrew Gallagher, Balaji Lakshminarayanan, Alex Alemi, Joshua Dillon
Oral
Thu 13:45 Quick Streaming Algorithms for Maximization of Monotone Submodular Functions in Linear Time
Alan Kuhnle
Oral Session
Thu 14:15 Deep Learning / High-dimensionality
Oral
Thu 14:15 Sketch based Memory for Neural Networks
Rina Panigrahy, Xin Wang, Manzil Zaheer
Oral
Thu 14:30 Associative Convolutional Layers
Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh Gupta
Oral
Thu 14:45 Deep Fourier Kernel for Self-Attentive Point Processes
Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie
Oral
Thu 15:00 Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression
Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan Tibshirani
Oral
Thu 15:15 A constrained risk inequality for general losses
John Duchi, Feng Ruan
Oral Session
Thu 15:15 Learning Theory
Oral
Thu 15:30 Misspecification in Prediction Problems and Robustness via Improper Learning
Annie Marsden, John Duchi, Gregory Valiant
Oral
Thu 15:45 Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs
Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani
Oral
Thu 16:00 Faster Kernel Interpolation for Gaussian Processes
Mohit Yadav, Daniel Sheldon, Cameron Musco
Session
AcceptedPapersParent