Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice

15 December 2017

Papers citing "Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice"

28 / 28 papers shown

Title
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems Huaqing Zhang Lesi Chen Jing Xu J.N. Zhang 78 0 0 28 Jan 2025
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 41 0 0 28 Jan 2025
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 44 1 0 09 Nov 2023
Statistical and Computational Guarantees for Influence Diagnostics Jillian R. Fisher Lang Liu Krishna Pillutla Y. Choi Zaïd Harchaoui TDI 29 0 0 08 Dec 2022
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties David Martínez-Rubio Sebastian Pokutta 29 9 0 26 Nov 2022
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 65 11 0 17 Jun 2022
On the fast convergence of minibatch heavy ball momentum Raghu Bollapragada Tyler Chen Rachel A. Ward 39 17 0 15 Jun 2022
Optimal Gradient Sliding and its Application to Distributed Optimization Under Similarity D. Kovalev Aleksandr Beznosikov Ekaterina Borodich Alexander Gasnikov G. Scutari 38 12 0 30 May 2022
On Acceleration of Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ekaterina Trimbach Edward Duc Hien Nguyen César A. Uribe 34 1 0 16 Apr 2022
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov Eduard A. Gorbunov Hugo Berard Nicolas Loizou 24 49 0 15 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 78 44 0 06 Feb 2022
Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum J. Kim Panos Toulis Anastasios Kyrillidis 28 8 0 11 Nov 2021
Acceleration in Distributed Optimization under Similarity Helena Lofstrom G. Scutari Tianyue Cao Alexander Gasnikov 32 26 0 24 Oct 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 38 61 0 29 Mar 2021
Accelerated, Optimal, and Parallel: Some Results on Model-Based Stochastic Optimization Karan N. Chadha Gary Cheng John C. Duchi 62 16 0 07 Jan 2021
Differentiable Programming à la Moreau Vincent Roulet Zaïd Harchaoui 23 5 0 31 Dec 2020
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 24 112 0 02 Oct 2020
Lagrangian Decomposition for Neural Network Verification Rudy Bunel Alessandro De Palma Alban Desmaison Krishnamurthy Dvijotham Pushmeet Kohli Philip Torr M. P. Kumar 19 50 0 24 Feb 2020
Cyanure: An Open-Source Toolbox for Empirical Risk Minimization for Python, C++, and soon more Julien Mairal 24 22 0 17 Dec 2019
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time Y. Lee Zhao Song Qiuyi Zhang 24 115 0 11 May 2019
Deep Neural Networks for Rotation-Invariance Approximation and Learning C. Chui Shao-Bo Lin Ding-Xuan Zhou 32 34 0 03 Apr 2019
Estimate Sequences for Stochastic Composite Optimization: Variance Reduction, Acceleration, and Robustness to Noise A. Kulunchakov Julien Mairal 34 44 0 25 Jan 2019
Understanding the Acceleration Phenomenon via High-Resolution Differential Equations Bin Shi S. Du Michael I. Jordan Weijie J. Su 17 254 0 21 Oct 2018
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes Rachel A. Ward Xiaoxia Wu Léon Bottou ODL 27 361 0 05 Jun 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 49 52 0 12 Feb 2018
An Inexact Variable Metric Proximal Point Algorithm for Generic Quasi-Newton Acceleration Hongzhou Lin Julien Mairal Zaïd Harchaoui 33 13 0 04 Oct 2016
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 93 737 0 19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 79 317 0 18 Feb 2014