Fast Stochastic Alternating Direction Method of Multipliers

16 August 2013

Papers citing "Fast Stochastic Alternating Direction Method of Multipliers"

34 / 34 papers shown

Title
Preconditioned Inexact Stochastic ADMM for Deep Model Shenglong Zhou Ouya Wang Ziyan Luo Yongxu Zhu Geoffrey Ye Li 86 0 0 15 Feb 2025
A General Continuous-Time Formulation of Stochastic ADMM and Its Variants Chris Junchi Li 69 0 0 22 Apr 2024
Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions T.-H. Hubert Chan Hao Xie Mengshi Zhao 67 1 0 14 Dec 2023
Regularization in network optimization via trimmed stochastic gradient descent with noisy label Kensuke Nakamura Bong-Soo Sohn Kyoung-Jae Won Byung-Woo Hong NoLa 51 0 0 21 Dec 2020
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 100 117 0 02 Oct 2020
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization Feihu Huang Songcan Chen Heng-Chiao Huang 38 38 0 04 Aug 2020
P-ADMMiRNN: Training RNN with Stable Convergence via An Efficient and Paralleled ADMM Approach Yu Tang Zhigang Kan Dequan Sun Jingjing Xiao Zhiquan Lai Linbo Qiao Dongsheng Li 30 0 0 10 Jun 2020
Distributed Machine Learning for Predictive Analytics in Mobile Edge Computing Based IoT Environments Prabath Abeysekara Hai Dong •. A. K. Qin 111 5 0 07 Jun 2020
Scalable Plug-and-Play ADMM with Convergence Guarantees Yu Sun Zihui Wu Xiaojian Xu B. Wohlberg Ulugbek S. Kamilov BDL 91 76 0 05 Jun 2020
Distributed Stochastic Nonconvex Optimization and Learning based on Successive Convex Approximation P. Lorenzo Simone Scardapane 53 2 0 30 Apr 2020
Stochastic batch size for adaptive regularization in deep network optimization Kensuke Nakamura Stefano Soatto Byung-Woo Hong ODL 44 6 0 14 Apr 2020
Stochastic Modified Equations for Continuous Limit of Stochastic ADMM Xiang Zhou Huizhuo Yuan C. J. Li Qingyun Sun 121 6 0 07 Mar 2020
Adaptive Weight Decay for Deep Neural Networks Kensuke Nakamura Byung-Woo Hong 63 43 0 21 Jul 2019
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding Menglei Zhang Zhou Liu Lei Yu 31 5 0 31 Dec 2018
Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization Feihu Huang Songcan Chen 69 21 0 08 Feb 2018
A Distributed Framework for the Construction of Transport Maps Diego A. Mesa Justin Tantiongloc Marcela Mendoza Todd P. Coleman 26 0 0 25 Jan 2018
On the Iteration Complexity Analysis of Stochastic Primal-Dual Hybrid Gradient Approach with High Probability Linbo Qiao Tianyi Lin Qi Qin Xicheng Lu 33 2 0 22 Jan 2018
Scalable Peaceman-Rachford Splitting Method with Proximal Terms Sen Na Mingyuan Ma Guangju Peng 21 2 0 14 Nov 2017
Fast Convolutional Sparse Coding in the Dual Domain Lama Affara Guohao Li Peter Wonka 20 0 0 27 Sep 2017
Convolutional Dictionary Learning: A Comparative Review and New Algorithms Cristina Garcia-Cardona B. Wohlberg 109 178 0 09 Sep 2017
Stochastic Primal-Dual Proximal ExtraGradient Descent for Compositely Regularized Optimization Tianyi Lin Linbo Qiao Teng Zhang Jiashi Feng Bofeng Zhang 28 8 0 20 Aug 2017
Accelerated Variance Reduced Stochastic ADMM Yuanyuan Liu Fanhua Shang James Cheng 69 41 0 11 Jul 2017
Convolutional Dictionary Learning: Acceleration and Convergence Il Yong Chun Jeffrey A. Fessler 96 94 0 03 Jul 2017
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications A. Chambolle Matthias Joachim Ehrhardt Peter Richtárik Carola-Bibiane Schönlieb 104 187 0 15 Jun 2017
Larger is Better: The Effect of Learning Rates Enjoyed by Stochastic Optimization with Progressive Variance Reduction Fanhua Shang 21 1 0 17 Apr 2017
Sparse Learning with Semi-Proximal-Based Strictly Contractive Peaceman-Rachford Splitting Method Sen Na Cho-Jui Hsieh 8 4 0 30 Dec 2016
Stochastic Alternating Direction Method of Multipliers with Variance Reduction for Nonconvex Optimization Feihu Huang Songcan Chen Zhaosong Lu 86 15 0 10 Oct 2016
Stochastic Variance-Reduced ADMM Shuai Zheng James T. Kwok 96 60 0 24 Apr 2016
Relaxed Linearized Algorithms for Faster X-Ray CT Image Reconstruction Hung Nien Jeffrey A. Fessler 56 41 0 14 Dec 2015
Scalable Stochastic Alternating Direction Method of Multipliers Shen-Yi Zhao Wu-Jun Li Zhi Zhou 68 21 0 12 Feb 2015
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 119 265 0 10 Sep 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 180 319 0 18 Feb 2014
Adaptive Stochastic Alternating Direction Method of Multipliers P. Zhao Jinwei Yang Tong Zhang Ping Li 88 19 0 16 Dec 2013
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 336 1,251 0 10 Sep 2013