JMLR · Scour

Learning with Linear Function Approximations in Mean-Field Control

Multiple Instance Verification

On the Convergence of Projected Policy Gradient for Any Constant Step Sizes

Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness

Linear Separation Capacity of Self-Supervised Representation Learning

Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes

Deep Out-of-Distribution Uncertainty Quantification via Weight Entropy Maximization

Efficiently Escaping Saddle Points in Bilevel Optimization

DisC2o-HD: Distributed causal inference with covariates shift for analyzing real-world high-dimensional data

Enhancing Graph Representation Learning with Localized Topological Features

Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents

Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback

A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation

Test-Time Training on Video Streams

Estimating Network-Mediated Causal Effects via Principal Components Network Regression

Selective Inference with Distributed Data

An Axiomatic Definition of Hierarchical Clustering

Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization

Locally Private Causal Inference for Randomized Experiments

From Sparse to Dense Functional Data in High Dimensions: Revisiting Phase Transitions from a Non-Asymptotic Perspective

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