Yunwen Lei | DeepAI

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∙ 05/26/2023

Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks

Recently, significant progress has been made in understanding the genera...

0 Puyu Wang, et al. ∙

∙ 02/24/2023

Generalization Analysis for Contrastive Representation Learning

Recently, contrastive learning has found impressive success in advancing...

0 Yunwen Lei, et al. ∙

∙ 12/16/2022

Generalization Bounds for Inductive Matrix Completion in Low-noise Settings

We study inductive matrix completion (matrix completion with side inform...

0 Antoine Ledent, et al. ∙

∙ 10/03/2022

On Stability and Generalization of Bilevel Optimization Problem

(Stochastic) bilevel optimization is a frequently encountered problem in...

0 Meng Ding, et al. ∙

∙ 09/16/2022

Stability and Generalization for Markov Chain Stochastic Gradient Methods

Recently there is a large amount of work devoted to the study of Markov ...

0 Puyu Wang, et al. ∙

∙ 09/09/2022

Differentially Private Stochastic Gradient Descent with Low-Noise

In this paper, by introducing a low-noise condition, we study privacy an...

0 Puyu Wang, et al. ∙

∙ 06/14/2022

Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems

Stochastic optimization has found wide applications in minimizing object...

0 Yunwen Lei, et al. ∙

∙ 01/22/2022

Differentially Private SGDA for Minimax Problems

Stochastic gradient descent ascent (SGDA) and its variants have been the...

0 Zhenhuan Yang, et al. ∙

∙ 11/23/2021

Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning

Pairwise learning refers to learning tasks where the loss function depen...

0 Zhenhuan Yang, et al. ∙

∙ 09/21/2021

Learning Interpretable Concept Groups in CNNs

We propose a novel training methodology – Concept Group Learning (CGL) –...

10 Saurabh Varshneya, et al. ∙

∙ 08/17/2021

Stability and Generalization for Randomized Coordinate Descent

Randomized coordinate descent (RCD) is a popular optimization algorithm ...

0 Puyu Wang, et al. ∙

∙ 05/31/2021

Fine-grained Generalization Analysis of Structured Output Prediction

In machine learning we often encounter structured output prediction prob...

0 Waleed Mustafa, et al. ∙

∙ 05/08/2021

Stability and Generalization of Stochastic Gradient Methods for Minimax Problems

Many machine learning problems can be formulated as minimax problems suc...

0 Yunwen Lei, et al. ∙

∙ 04/29/2021

Fine-grained Generalization Analysis of Vector-valued Learning

Many fundamental machine learning tasks can be formulated as a problem o...

0 Liang Wu, et al. ∙

∙ 01/22/2021

Differentially Private SGD with Non-Smooth Loss

In this paper, we are concerned with differentially private SGD algorith...

0 Puyu Wang, et al. ∙

∙ 11/04/2020

Stochastic Hard Thresholding Algorithms for AUC Maximization

In this paper, we aim to develop stochastic hard thresholding algorithms...

0 Zhenhuan Yang, et al. ∙

∙ 06/15/2020

Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent

Recently there are a considerable amount of work devoted to the study of...

0 Yunwen Lei, et al. ∙

∙ 11/19/2019

On Performance Estimation in Automatic Algorithm Configuration

Over the last decade, research on automated parameter tuning, often refe...

0 Shengcai Liu, et al. ∙

∙ 06/14/2019

Stochastic Proximal AUC Maximization

In this paper we consider the problem of maximizing the Area under the R...

0 Yunwen Lei, et al. ∙

∙ 05/29/2019

Improved Generalisation Bounds for Deep Learning Through L^∞ Covering Numbers

Using proof techniques involving L^∞ covering numbers, we show generalis...

0 Antoine Ledent, et al. ∙

∙ 05/24/2019

A Generalization Error Bound for Multi-class Domain Generalization

Domain generalization is the problem of assigning labels to an unlabeled...

0 Aniket Anand Deshmukh, et al. ∙

∙ 02/03/2019

Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions

Stochastic gradient descent (SGD) is a popular and efficient method with...

0 Yunwen Lei, et al. ∙

∙ 02/18/2018

Convergence of Online Mirror Descent Algorithms

In this paper we consider online mirror descent (OMD) algorithms, a clas...

0 Yunwen Lei, et al. ∙

∙ 10/06/2015

Local Rademacher Complexity Bounds based on Covering Numbers

This paper provides a general result on controlling local Rademacher com...

0 Yunwen Lei, et al. ∙

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