Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications

15 June 2017

A. Chambolle

Matthias Joachim Ehrhardt

Peter Richtárik

Carola-Bibiane Schönlieb

ArXiv PDF HTML

Papers citing "Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications"

50 / 51 papers shown

Title
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise Shuyao Li Sushrut Karmalkar Ilias Diakonikolas Jelena Diakonikolas OOD 47 0 0 11 Nov 2024
A Primal-dual algorithm for image reconstruction with ICNNs Hok Shing Wong Matthias Joachim Ehrhardt Subhadip Mukherjee 26 1 0 16 Oct 2024
Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization Yue Xie Jiawen Bi Hongcheng Liu 18 0 0 27 Jun 2024
Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging C. Tsai Hao-Chung Cheng Yen-Huan Li 33 0 0 05 Nov 2023
Enhanced Federated Optimization: Adaptive Unbiased Sampling with Reduced Variance Dun Zeng Zenglin Xu Yu Pan Xu Luo Qifan Wang Xiaoying Tang FedML 17 1 0 04 Oct 2023
Towards a Better Theoretical Understanding of Independent Subnetwork Training Egor Shulgin Peter Richtárik AI4CE 28 6 0 28 Jun 2023
Empirical Risk Minimization with Shuffled SGD: A Primal-Dual Perspective and Improved Bounds Xu Cai Cheuk Yin Lin Jelena Diakonikolas FedML 31 5 0 21 Jun 2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization Cheuk Yin Lin Chaobing Song Jelena Diakonikolas 19 5 0 28 Mar 2023
Restarts subject to approximate sharpness: A parameter-free and optimal scheme for first-order methods Ben Adcock Matthew J. Colbrook Maksym Neyra-Nesterenko 29 2 0 05 Jan 2023
Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising Junqi Tang Matthias Joachim Ehrhardt Carola-Bibiane Schönlieb 28 0 0 02 Aug 2022
Fast Kernel Methods for Generic Lipschitz Losses via $p$ -Sparsified Sketches T. Ahmad Pierre Laforgue Florence dÁlché-Buc 19 5 0 08 Jun 2022
Operator Sketching for Deep Unrolling Networks Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 24 0 0 21 Mar 2022
Data-Consistent Local Superresolution for Medical Imaging Junqi Tang SupR 30 0 0 22 Feb 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 20 0 0 21 Feb 2022
Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods Yujia Jin Aaron Sidford Kevin Tian 19 30 0 09 Feb 2022
On the Complexity of a Practical Primal-Dual Coordinate Method Ahmet Alacaoglu V. Cevher Stephen J. Wright 21 12 0 19 Jan 2022
A Stochastic Bregman Primal-Dual Splitting Algorithm for Composite Optimization Antonio Silveti-Falls C. Molinari Jalal Fadili 24 8 0 22 Dec 2021
A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin J. Latz Chenguang Liu Carola-Bibiane Schönlieb 18 9 0 07 Dec 2021
Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming Haihao Lu Jinwen Yang 14 6 0 10 Nov 2021
Coordinate Linear Variance Reduction for Generalized Linear Programming Chaobing Song Cheuk Yin Lin Stephen J. Wright Jelena Diakonikolas 24 12 0 02 Nov 2021
WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditions Matthew J. Colbrook 26 2 0 24 Oct 2021
Stochastic Primal-Dual Deep Unrolling Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 24 4 0 19 Oct 2021
Accelerated nonlinear primal-dual hybrid gradient methods with applications to supervised machine learning Jérome Darbon G. P. Langlois 28 4 0 24 Sep 2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums Chaobing Song Stephen J. Wright Jelena Diakonikolas 67 16 0 26 Feb 2021
Cyclic Coordinate Dual Averaging with Extrapolation Chaobing Song Jelena Diakonikolas 27 6 0 26 Feb 2021
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 58 68 0 16 Feb 2021
Maximum-Likelihood Quantum State Tomography by Soft-Bayes Chien-Ming Lin Yu-Ming Hsu Yen-Huan Li 27 1 0 31 Dec 2020
ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering Xiang Fang Yuchong Hu Pan Zhou Dapeng Oliver Wu 23 34 0 20 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 32 0 0 26 Aug 2020
Multi-modality imaging with structure-promoting regularisers Matthias Joachim Ehrhardt MedIm 13 10 0 22 Jul 2020
Random extrapolation for primal-dual coordinate descent Ahmet Alacaoglu Olivier Fercoq V. Cevher 14 16 0 13 Jul 2020
A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems Junqi Tang Mike Davies 9 17 0 20 Jun 2020
A Better Alternative to Error Feedback for Communication-Efficient Distributed Learning Samuel Horváth Peter Richtárik 16 61 0 19 Jun 2020
Analysis of Stochastic Gradient Descent in Continuous Time J. Latz 28 38 0 15 Apr 2020
A New Randomized Primal-Dual Algorithm for Convex Optimization with Optimal Last Iterate Rates Quoc Tran-Dinh Deyi Liu 72 4 0 03 Mar 2020
High-Performance Statistical Computing in the Computing Environments of the 2020s Seyoon Ko Hua Zhou Jin J. Zhou Joong-Ho Won 15 8 0 07 Jan 2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems Junqi Tang K. Egiazarian Mohammad Golbabaee Mike Davies 25 30 0 22 Oct 2019
Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip Nicolas Loizou 19 5 0 26 Sep 2019
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham T. Dzung Lam M. Nguyen 19 49 0 08 Jul 2019
Expected Sarsa( $λ$ ) with Control Variate for Variance Reduction Long Yang Yu Zhang Jun Wen Qian Zheng Pengfei Li Gang Pan 19 0 0 25 Jun 2019
Hybrid Stochastic Gradient Descent Algorithms for Stochastic Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham Dzung Phan Lam M. Nguyen 22 54 0 15 May 2019
Convergence Analysis of Inexact Randomized Iterative Methods Nicolas Loizou Peter Richtárik 14 21 0 19 Mar 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 11 139 0 15 Feb 2019
SGD: General Analysis and Improved Rates Robert Mansel Gower Nicolas Loizou Xun Qian Alibek Sailanbayev Egor Shulgin Peter Richtárik 23 375 0 27 Jan 2019
SAGA with Arbitrary Sampling Xun Qian Zheng Qu Peter Richtárik 29 25 0 24 Jan 2019
SEGA: Variance Reduction via Gradient Sketching Filip Hanzely Konstantin Mishchenko Peter Richtárik 25 71 0 09 Sep 2018
Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning Matthias Joachim Ehrhardt P. Markiewicz Carola-Bibiane Schönlieb 13 30 0 21 Aug 2018
A Constant Step Stochastic Douglas-Rachford Algorithm with Application to Non Separable Regularizations Adil Salim Pascal Bianchi W. Hachem 10 2 0 03 Apr 2018
On the Iteration Complexity Analysis of Stochastic Primal-Dual Hybrid Gradient Approach with High Probability Linbo Qiao Tianyi Lin Qi Qin Xicheng Lu 11 1 0 22 Jan 2018
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments Radoslav Harman Lenka Filová Peter Richtárik 24 51 0 17 Jan 2018