activity
20192023
most citedSimple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

10 citations · 22 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023★ 2 cited

Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks

Puyu Wang, Yunwen Lei, Di Wang +2

Recently, significant progress has been made in understanding the generalization of neural networks (NNs) trained by gradient descent (GD) using the algorithmic stability approach.…

stat.ML2022★ 3 cited

Stability and Generalization for Markov Chain Stochastic Gradient Methods

Puyu Wang, Yunwen Lei, Yiming Ying +1

Recently there is a large amount of work devoted to the study of Markov chain stochastic gradient methods (MC-SGMs) which mainly focus on their convergence analysis for solving min…

stat.ML2022★ 1 cited

Differentially Private Stochastic Gradient Descent with Low-Noise

Puyu Wang, Yunwen Lei, Yiming Ying +1

Modern machine learning algorithms aim to extract fine-grained information from data to provide accurate predictions, which often conflicts with the goal of privacy protection. Thi…

cs.LG2021★ 10 cited

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

Zhenhuan Yang, Yunwen Lei, Puyu Wang +2

Pairwise learning refers to learning tasks where the loss function depends on a pair of instances. It instantiates many important machine learning tasks such as bipartite ranking a…

cs.LG2021

Stability and Generalization for Randomized Coordinate Descent

Puyu Wang, Liang Wu, Yunwen Lei

Randomized coordinate descent (RCD) is a popular optimization algorithm with wide applications in solving various machine learning problems, which motivates a lot of theoretical an…

stat.ML2021★ 5 cited

Differentially Private SGD with Non-Smooth Losses

Puyu Wang, Yunwen Lei, Yiming Ying +1

In this paper, we are concerned with differentially private {stochastic gradient descent (SGD)} algorithms in the setting of stochastic convex optimization (SCO). Most of the exist…

stat.ML2019★ 1 cited

Differential Privacy for Sparse Classification Learning

Puyu Wang, Hai Zhang

In this paper, we present a differential privacy version of convex and nonconvex sparse classification approach. Based on alternating direction method of multiplier (ADMM) algorith…