Yunwen Lei

Affiliations

The University of Hong Kong

papers

112

total citations

papers (12)

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

NEURIPS 2021arXiv

citations

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks

NEURIPS 2022arXiv

citations

Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks

NEURIPS 2022arXiv

citations

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification

NEURIPS 2025arXiv

citations

Fine-grained Generalization Analysis of Inductive Matrix Completion

NEURIPS 2021

citations

Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning

AAAI 2025arXiv

citations

Yunwen Lei

Affiliations

papers (12)

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks

Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks

Stability and Generalization for Markov Chain Stochastic Gradient Methods

Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems

Generalization Analysis for Deep Contrastive Representation Learning

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms

Sharper Generalization Bounds for Pairwise Learning

Generalization Guarantee of SGD for Pairwise Learning

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification

Fine-grained Generalization Analysis of Inductive Matrix Completion

Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning

papers (12)

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks

Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks

Stability and Generalization for Markov Chain Stochastic Gradient Methods

Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems

Generalization Analysis for Deep Contrastive Representation Learning

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms

Sharper Generalization Bounds for Pairwise Learning

Generalization Guarantee of SGD for Pairwise Learning

Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification

Fine-grained Generalization Analysis of Inductive Matrix Completion

Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning