Papers
Nearly Minimax Discrete Distribution Estimation in Kullback-Leibler Divergence with High Probability
Dirk van der Hoeven, Julia Olkhovskaya, Tim van Erven
Strategy-robust Online Learning in Contextual Pricing
Joon Suk Huh, Kirthevasan Kandasamy
Reusing Samples in Variance Reduction
Yujia Jin, Ishani Karmarkar, Aaron Sidford et al.
On Characterizations for Language Generation: Interplay of Hallucinations, Breadth, and Stability
Alkis Kalavasis, Anay Mehrotra, Grigoris Velegkas
Optimal L2 Regularization in High-dimensional Continual Linear Regression
Gilad Karpel, Edward Moroshko, Ran Levinstein et al.
The Planted Number Partitioning Problem
Eren C. Kizildag
DS-Compatible Log-Linear Reliability with KL-Prox EM: Monotone Ascent, Identifiability, and Generalization
Shiva Koreddi, Sravani Sowrupilli
Differentially Private Bilevel Optimization
Guy Kornowski
Learning with Monotone Adversarial Corruptions
Kasper Green Larsen, Chirag Pabbaraju, Abhishek Shetty
Improved Replicable Boosting with Majority-of-Majorities
Kasper Green Larsen, Markus Engelund Mathiasen, Clement Svendsen
No Scale Sensitive Dimension for Distribution Learning
Tosca Lechner, Shai Ben-David
Accelerated Mirror Descent for Non-Euclidean Star-convex Functions
Clement LEZANE, Sophie Langer, Wouter M Koolen
Sample Complexity Bounds for Linear Constrained MDPs with a Generative Model
Xingtu Liu, Lin F. Yang, Sharan Vaswani
Efficient Opportunistic Approachability
Teodor Vanislavov Marinov, Mehryar Mohri, Princewill Okoroafor et al.
Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
Diego Martinez-Taboada, Tomás González, Aaditya Ramdas
Online Markov Decision Processes with Terminal Law Constraints
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard et al.
Online Covering with Multiple Experts
Kim Thang Nguyen
How to Set β_1, β_2 in Adam: An Online Learning Perspective
Quan M. Nguyen
A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes
Alireza F. Pour, Shai Ben-David
Large Average Subtensor Problem: Ground-State, Algorithms, and Algorithmic Barriers
Abhishek Hegade K. R., Eren C. Kizildag
Optimal Bounds for Tyler’s M-Estimator for Elliptical Distributions
Akshay Ramachandran, Lap Chi Lau
Recycling History: Efficient Recommendations from Contextual Dueling Bandits
Suryanarayana Sankagiri, Jalal Etesami, Pouria Fatemi et al.
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
Matan Schliserman, Tomer Koren