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05/27/2023
Faster Margin Maximization Rates for Generic Optimization Methods
First-order optimization methods tend to inherently favor certain soluti...
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05/03/2023
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features
The support vector machine (SVM) is a supervised learning algorithm that...
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03/13/2023
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
We provide a unified framework, applicable to a general family of convex...
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02/19/2023
Estimating Optimal Policy Value in General Linear Contextual Bandits
In many bandit problems, the maximal reward achievable by a policy is of...
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10/17/2022
Adaptive Oracle-Efficient Online Learning
The classical algorithms for online learning and decision-making have th...
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10/10/2022
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
Data augmentation (DA) is a powerful workhorse for bolstering performanc...
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04/08/2022
The Complexity of Infinite-Horizon General-Sum Stochastic Games
We study the complexity of computing stationary Nash equilibrium (NE) in...
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11/09/2021
Harmless interpolation in regression and classification with structured features
Overparametrized neural networks tend to perfectly fit noisy training da...
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11/08/2021
Universal and data-adaptive algorithms for model selection in linear contextual bandits
Model selection in contextual bandits is an important complementary prob...
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09/27/2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective
State-of-the-art deep learning classifiers are heavily overparameterized...
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09/06/2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning
The rapid recent progress in machine learning (ML) has raised a number o...
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06/28/2021
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits
We introduce the "inverse bandit" problem of estimating the rewards of a...
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06/21/2021
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
The growing literature on "benign overfitting" in overparameterized mode...
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12/03/2020
On the Impossibility of Convergence of Mixed Strategies with No Regret Learning
We study convergence properties of the mixed strategies that result from...
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11/19/2020
Online Model Selection for Reinforcement Learning with Function Approximation
Deep reinforcement learning has achieved impressive successes yet often ...
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09/22/2020
On the proliferation of support vectors in high dimensions
The support vector machine (SVM) is a well-established classification me...
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05/16/2020
Classification vs regression in overparameterized regimes: Does the loss function matter?
We compare classification and regression tasks in the overparameterized ...
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05/28/2019
Robust Commitments and Partial Reputation
Agents rarely act in isolation -- their behavioral history, in particula...
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05/24/2019
OSOM: A Simultaneously Optimal Algorithm for Multi-Armed and Linear Contextual Bandits
We consider the stochastic linear (multi-armed) contextual bandit proble...
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03/21/2019
Harmless interpolation of noisy data in regression
A continuing mystery in understanding the empirical success of deep neur...
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11/30/2018
Understanding Unequal Gender Classification Accuracy from Face Images
Recent work shows unequal performance of commercial face classification ...
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05/22/2018
Best of many worlds: Robust model selection for online supervised learning
We introduce algorithms for online, full-information prediction that are...
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07/19/2017