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

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

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Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization Cheuk Yin Lin Chaobing Song Jelena Diakonikolas 17 4 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 14 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 20 0 0 02 Aug 2022
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Operator Sketching for Deep Unrolling Networks Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 13 0 0 21 Mar 2022
Data-Consistent Local Superresolution for Medical Imaging Junqi Tang SupR 12 0 0 22 Feb 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness Beomsu Kim Junghoon Seo AAML 12 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 11 30 0 09 Feb 2022
On the Complexity of a Practical Primal-Dual Coordinate Method Ahmet Alacaoglu V. Cevher Stephen J. Wright 13 10 0 19 Jan 2022
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A Continuous-time Stochastic Gradient Descent Method for Continuous Data Kexin Jin J. Latz Chenguang Liu Carola-Bibiane Schönlieb 10 9 0 07 Dec 2021
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Coordinate Linear Variance Reduction for Generalized Linear Programming Chaobing Song Cheuk Yin Lin Stephen J. Wright Jelena Diakonikolas 16 12 0 02 Nov 2021
WARPd: A linearly convergent first-order method for inverse problems with approximate sharpness conditions Matthew J. Colbrook 8 2 0 24 Oct 2021
Stochastic Primal-Dual Deep Unrolling Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 6 4 0 19 Oct 2021
Accelerated nonlinear primal-dual hybrid gradient methods with applications to supervised machine learning Jérome Darbon G. P. Langlois 23 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 59 16 0 26 Feb 2021
Cyclic Coordinate Dual Averaging with Extrapolation Chaobing Song Jelena Diakonikolas 20 6 0 26 Feb 2021
Stochastic Variance Reduction for Variational Inequality Methods Ahmet Alacaoglu Yura Malitsky 51 68 0 16 Feb 2021
Maximum-Likelihood Quantum State Tomography by Soft-Bayes Chien-Ming Lin Yu-Ming Hsu Yen-Huan Li 10 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 17 34 0 20 Nov 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 19 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 6 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 8 61 0 19 Jun 2020
Analysis of Stochastic Gradient Descent in Continuous Time J. Latz 17 37 0 15 Apr 2020
A New Randomized Primal-Dual Algorithm for Convex Optimization with Optimal Last Iterate Rates Quoc Tran-Dinh Deyi Liu 64 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 13 8 0 07 Jan 2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems Junqi Tang K. Egiazarian Mohammad Golbabaee Mike Davies 15 30 0 22 Oct 2019
Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip Nicolas Loizou 13 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 13 48 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 14 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 14 53 0 15 May 2019
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SGD: General Analysis and Improved Rates Robert Mansel Gower Nicolas Loizou Xun Qian Alibek Sailanbayev Egor Shulgin Peter Richtárik 17 368 0 27 Jan 2019
SAGA with Arbitrary Sampling Xun Qian Zheng Qu Peter Richtárik 21 25 0 24 Jan 2019
SEGA: Variance Reduction via Gradient Sketching Filip Hanzely Konstantin Mishchenko Peter Richtárik 10 71 0 09 Sep 2018
Faster PET Reconstruction with Non-Smooth Priors by Randomization and Preconditioning Matthias Joachim Ehrhardt P. Markiewicz Carola-Bibiane Schönlieb 8 29 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 9 1 0 22 Jan 2018
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments Radoslav Harman Lenka Filová Peter Richtárik 16 51 0 17 Jan 2018