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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...
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02/24/2023
Generalization Analysis for Contrastive Representation Learning
Recently, contrastive learning has found impressive success in advancing...
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12/16/2022
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings
We study inductive matrix completion (matrix completion with side inform...
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10/03/2022
On Stability and Generalization of Bilevel Optimization Problem
(Stochastic) bilevel optimization is a frequently encountered problem in...
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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 ...
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09/09/2022
Differentially Private Stochastic Gradient Descent with Low-Noise
In this paper, by introducing a low-noise condition, we study privacy an...
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06/14/2022
Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems
Stochastic optimization has found wide applications in minimizing object...
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01/22/2022
Differentially Private SGDA for Minimax Problems
Stochastic gradient descent ascent (SGDA) and its variants have been the...
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11/23/2021
Simple Stochastic and Online Gradient Descent Algorithms for Pairwise Learning
Pairwise learning refers to learning tasks where the loss function depen...
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09/21/2021
Learning Interpretable Concept Groups in CNNs
We propose a novel training methodology – Concept Group Learning (CGL) –...
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08/17/2021
Stability and Generalization for Randomized Coordinate Descent
Randomized coordinate descent (RCD) is a popular optimization algorithm ...
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05/31/2021
Fine-grained Generalization Analysis of Structured Output Prediction
In machine learning we often encounter structured output prediction prob...
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05/08/2021
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems
Many machine learning problems can be formulated as minimax problems suc...
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04/29/2021
Fine-grained Generalization Analysis of Vector-valued Learning
Many fundamental machine learning tasks can be formulated as a problem o...
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01/22/2021
Differentially Private SGD with Non-Smooth Loss
In this paper, we are concerned with differentially private SGD algorith...
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11/04/2020
Stochastic Hard Thresholding Algorithms for AUC Maximization
In this paper, we aim to develop stochastic hard thresholding algorithms...
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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...
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11/19/2019
On Performance Estimation in Automatic Algorithm Configuration
Over the last decade, research on automated parameter tuning, often refe...
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06/14/2019
Stochastic Proximal AUC Maximization
In this paper we consider the problem of maximizing the Area under the R...
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05/29/2019
Improved Generalisation Bounds for Deep Learning Through L^∞ Covering Numbers
Using proof techniques involving L^∞ covering numbers, we show generalis...
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05/24/2019
A Generalization Error Bound for Multi-class Domain Generalization
Domain generalization is the problem of assigning labels to an unlabeled...
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02/03/2019
Stochastic Gradient Descent for Nonconvex Learning without Bounded Gradient Assumptions
Stochastic gradient descent (SGD) is a popular and efficient method with...
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02/18/2018
Convergence of Online Mirror Descent Algorithms
In this paper we consider online mirror descent (OMD) algorithms, a clas...
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10/06/2015
