Shixiang Chen | DeepAI

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∙ 09/18/2023

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data

Federated learning is an emerging distributed machine learning method, e...

0 Hao Sun, et al. ∙

∙ 05/19/2023

Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape

In federated learning (FL), a cluster of local clients are chaired under...

0 Yan Sun, et al. ∙

∙ 03/31/2023

Decentralized Weakly Convex Optimization Over the Stiefel Manifold

We focus on a class of non-smooth optimization problems over the Stiefel...

0 Jinxin Wang, et al. ∙

∙ 03/01/2023

AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks

Sharpness aware minimization (SAM) optimizer has been extensively explor...

0 Hao Sun, et al. ∙

∙ 05/24/2022

Penalized Proximal Policy Optimization for Safe Reinforcement Learning

Safe reinforcement learning aims to learn the optimal policy while satis...

16 Linrui zhang, et al. ∙

∙ 03/17/2022

Do We Really Need a Learnable Classifier at the End of Deep Neural Network?

Modern deep neural networks for classification usually jointly learn a b...

1 Yibo Yang, et al. ∙

∙ 02/14/2021

Decentralized Riemannian Gradient Descent on the Stiefel Manifold

We consider a distributed non-convex optimization where a network of age...

0 Shixiang Chen, et al. ∙

∙ 01/22/2021

On the Local Linear Rate of Consensus on the Stiefel Manifold

We study the convergence properties of Riemannian gradient method for so...

0 Shixiang Chen, et al. ∙

∙ 07/18/2020

A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis

Spectral clustering is one of the fundamental unsupervised learning meth...

11 Zhongruo Wang, et al. ∙

∙ 05/05/2020

Manifold Proximal Point Algorithms for Dual Principal Component Pursuit and Orthogonal Dictionary Learning

We consider the problem of maximizing the ℓ_1 norm of a linear map over ...

0 Shixiang Chen, et al. ∙

∙ 04/28/2020

Distributed Projected Subgradient Method for Weakly Convex Optimization

The stochastic subgradient method is a widely-used algorithm for solving...

0 Shixiang Chen, et al. ∙

∙ 11/12/2019

Nonsmooth Optimization over Stiefel Manifold: Riemannian Subgradient Methods

Nonsmooth Riemannian optimization is a still under explored subfield of ...

0 Xiao Li, et al. ∙

∙ 03/27/2019

An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA

Sparse principal component analysis (PCA) and sparse canonical correlati...

0 Shixiang Chen, et al. ∙

∙ 11/02/2018

Proximal Gradient Method for Manifold Optimization

This paper considers manifold optimization problems with nonsmooth and n...

0 Shixiang Chen, et al. ∙

∙ 12/29/2016

Geometric descent method for convex composite minimization

In this paper, we extend the geometric descent method recently proposed ...

0 Shixiang Chen, et al. ∙

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