Papers
Regret Minimization with Adaptive Opponents in Repeated Games
Mingyang Liu, Asuman Ozdaglar, Tiancheng Yu et al.
Online Learning for Uninformed Markov Games: Empirical Nash-Value Regret and Non-Stationarity Adaptation
Junyan Liu, Haipeng Luo, Zihan Zhang et al.
Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity
Haitong Liu, Deepak Narayanan Sridharan, David Steurer et al.
Optimal Learning Rate Schedules under Functional Scaling Laws: Power Decay and Warmup–Stable–Decay (Extended Abstract)
Binghui Li, Zilin Wang, Fengling Chen et al.
Second-Order Bounds for $[0,1]$-Valued Regression via Betting Loss
Yinan Li, Sungjoon Yoon, Ethan Huang et al.
Self-Concordant Perturbations for Linear Bandits
Lucas Lévy, Jean-Lou Valeau, Arya Akhavan et al.
A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak–Ruppert Averaging
Wei-Cheng Lee, Francesco Orabona
Blackwell Approachability and Gradient Equilibrium are Equivalent
Brian W. Lee, Nika Haghtalab, Michael I. Jordan et al.
Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning
Harin Lee, Min-hwan Oh
Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader
Jongyeong Lee, Junya Honda, Shinji Ito et al.
How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
Kuo-Wei Lai, Guanghui Wang, Molei Tao et al.
On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA
Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar et al.
A Distribution Testing Approach to Clustering Distributions
Gunjan Kumar, Yash Pote, Jonathan Scarlett
Clipping the Price of Adaptivity at the Tail
Itai Kreisler, Yair Carmon, Oliver Hinder
Ambiguous Online Learning
Vanessa Kosoy
Overlap Analysis of the Shortest Path Problem: Local Search, Landscapes, and Franz-Parisi Potential
Frederic Koehler, Joonhyung Shin
Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift
Shyamal Patel, Adam Klivans, Konstantinos Stavropoulos et al.
Sandwiching Polynomials for Geometric Concepts with Low Intrinsic Dimension
Adam Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
Recursively Enumerably Representable Classes and Computable Versions of the Fundamental Theorem of Statistical Learning
David Kattermann, Lothar Sebastian Krapp
Fast, Parallel, Query-Efficient Binary Classification
Ishani Karmarkar, Liam O’Carroll, Aaron Sidford
Can SGD Select Good Fishermen? Local Convergence under Self-Selection Biases (Extended Abstract)
Alkis Kalavasis, Anay Mehrotra, Felix Zhou
Ripple Mechanisms for Discrete and Private Statistics
Matthew Joseph, Alex Kulesza, Yuyan Wang et al.
Avoiding exp($k^*$) Scaling for Thompson Sampling in Combinatorial Semi-Bandits: From Multiple Seeds to a Single Seed
Tianyuan Jin, Heyang Zhao, Vincent Y. F. Tan et al.
Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization
Ruichen Jiang, Zakaria Mhammedi, Mehryar Mohri et al.