Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization

10 September 2014

Papers citing "Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization"

34 / 34 papers shown

Title
Contractivity and linear convergence in bilinear saddle-point problems: An operator-theoretic approach Colin Dirren Mattia Bianchi Panagiotis D. Grontas John Lygeros Florian Dorfler 36 0 0 18 Oct 2024
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 33 179 0 28 Mar 2022
Decentralized Stochastic Variance Reduced Extragradient Method Luo Luo Haishan Ye 21 7 0 01 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
Cyclic Coordinate Dual Averaging with Extrapolation Chaobing Song Jelena Diakonikolas 27 6 0 26 Feb 2021
First-Order Methods for Convex Optimization Pavel Dvurechensky Mathias Staudigl Shimrit Shtern ODL 23 25 0 04 Jan 2021
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems Jiawei Zhang Peijun Xiao Ruoyu Sun Zhi-Quan Luo 33 97 0 29 Oct 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi Ma 53 23 0 18 Jun 2020
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 32 122 0 23 Jun 2019
Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model Tong Wang Qihang Lin 30 19 0 10 May 2019
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates Kaiwen Zhou Fanhua Shang James Cheng 14 74 0 28 Jun 2018
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity S. Du Wei Hu 58 120 0 05 Feb 2018
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications A. Chambolle Matthias Joachim Ehrhardt Peter Richtárik Carola-Bibiane Schönlieb 29 184 0 15 Jun 2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization Tomoya Murata Taiji Suzuki OffRL 30 28 0 01 Mar 2017
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization Bo Liu Xiaotong Yuan Lezi Wang Qingshan Liu Dimitris N. Metaxas 16 16 0 01 Mar 2017
Communication-Efficient Algorithms for Decentralized and Stochastic Optimization Guanghui Lan Soomin Lee Yi Zhou 35 218 0 14 Jan 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data Jialei Wang J. Lee M. Mahdavi Mladen Kolar Nathan Srebro 18 50 0 10 Oct 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method Lihua Lei Michael I. Jordan 21 95 0 12 Sep 2016
Fast and Simple Optimization for Poisson Likelihood Models Niao He Zaïd Harchaoui Yichen Wang Le Song 15 14 0 03 Aug 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems B. Palaniappan Francis R. Bach 18 210 0 20 May 2016
A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization Shun Zheng Jialei Wang Fen Xia Wenyuan Xu Tong Zhang 13 22 0 13 Apr 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 575 0 18 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 16 389 0 17 Mar 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 38 172 0 30 Dec 2015
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework Virginia Smith Simone Forte Michael I. Jordan Martin Jaggi 23 28 0 13 Dec 2015
An optimal randomized incremental gradient method Guanghui Lan Yi Zhou 23 220 0 08 Jul 2015
Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems Zhanxing Zhu Amos J. Storkey ODL 19 19 0 12 Jun 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 53 97 0 27 Feb 2015
Communication-Efficient Distributed Optimization of Self-Concordant Empirical Loss Yuchen Zhang Lin Xiao 33 72 0 01 Jan 2015
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 30 58 0 21 Nov 2014
A Lower Bound for the Optimization of Finite Sums Alekh Agarwal Léon Bottou 28 124 0 02 Oct 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 84 736 0 19 Mar 2014
Minimizing Finite Sums with the Stochastic Average Gradient Mark W. Schmidt Nicolas Le Roux Francis R. Bach 52 1,243 0 10 Sep 2013
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes Ohad Shamir Tong Zhang 101 570 0 08 Dec 2012