JMLR · Scour

Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles

Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos

Principled Penalty-based Methods for Bilevel Reinforcement Learning and RLHF

Score-based Causal Representation Learning: Linear and General Transformations

Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers

DRM Revisited: A Complete Error Analysis

Degree of Interference: A General Framework For Causal Inference Under Interference

Posterior and Variational Inference for Deep Neural Networks with Heavy-Tailed Weights

Quantifying the Effectiveness of Linear Preconditioning in Markov Chain Monte Carlo

Sparse SVM with Hard-Margin Loss: a Newton-Augmented Lagrangian Method in Reduced Dimensions

Maximum Causal Entropy IRL in Mean-Field Games and GNEP Framework for Forward RL

On Model Identification and Out-of-Sample Prediction of PCR with Applications to Synthetic Controls

Bayesian Scalar-on-Image Regression with a Spatially Varying Single-layer Neural Network Prior

Last-iterate Convergence of Shuffling Momentum Gradient Method under the Kurdyka-Lojasiewicz Inequality

Physics-informed Kernel Learning

BitNet: 1-bit Pre-training for Large Language Models

Modelling Populations of Interaction Networks via Distance Metrics

Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning

Transformers from Diffusion: A Unified Framework for Neural Message Passing

Actor-Critic learning for mean-field control in continuous time

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