Tight Complexity Bounds for Optimizing Composite Objectives

25 May 2016

Papers citing "Tight Complexity Bounds for Optimizing Composite Objectives"

40 / 40 papers shown

Title
Tuning-Free Stochastic Optimization Ahmed Khaled Chi Jin 32 7 0 12 Feb 2024
Memory-Query Tradeoffs for Randomized Convex Optimization Xinyu Chen Binghui Peng 36 6 0 21 Jun 2023
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis Dachao Lin Yuze Han Haishan Ye Zhihua Zhang 25 11 0 15 Apr 2023
Sublinear Convergence Rates of Extragradient-Type Methods: A Survey on Classical and Recent Developments Quoc Tran-Dinh 35 7 0 30 Mar 2023
Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing Kunal Jain J. PrabuchandranK. Tejas Bodas 27 2 0 21 Mar 2023
Stochastic Steffensen method Minda Zhao Zehua Lai Lek-Heng Lim ODL 15 3 0 28 Nov 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization Ali Kavis Stratis Skoulakis Kimon Antonakopoulos L. Dadi V. Cevher 24 15 0 03 Nov 2022
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 55 11 0 17 Jun 2022
How catastrophic can catastrophic forgetting be in linear regression? Itay Evron E. Moroshko Rachel A. Ward Nati Srebro Daniel Soudry CLL 27 48 0 19 May 2022
Efficient Convex Optimization Requires Superlinear Memory A. Marsden Vatsal Sharan Aaron Sidford Gregory Valiant 29 14 0 29 Mar 2022
Distributionally Robust Optimization via Ball Oracle Acceleration Y. Carmon Danielle Hausler 18 11 0 24 Mar 2022
Stochastic Primal-Dual Deep Unrolling Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 24 4 0 19 Oct 2021
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization Kaiwen Zhou Anthony Man-Cho So James Cheng 19 1 0 30 Sep 2021
Stochastic Bias-Reduced Gradient Methods Hilal Asi Y. Carmon A. Jambulapati Yujia Jin Aaron Sidford 24 29 0 17 Jun 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 33 61 0 29 Mar 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 43 14 0 21 Mar 2021
Machine Unlearning via Algorithmic Stability Enayat Ullah Tung Mai Anup B. Rao Ryan Rossi R. Arora 32 101 0 25 Feb 2021
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely Boxin Zhao Mladen Kolar FedML 27 52 0 19 Feb 2021
Lower Bounds and Optimal Algorithms for Personalized Federated Learning Filip Hanzely Slavomír Hanzely Samuel Horváth Peter Richtárik FedML 50 186 0 05 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 31 126 0 25 Aug 2020
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization Chaobing Song Yong Jiang Yi Ma 53 23 0 18 Jun 2020
Minibatch vs Local SGD for Heterogeneous Distributed Learning Blake E. Woodworth Kumar Kshitij Patel Nathan Srebro FedML 22 199 0 08 Jun 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 35 17 0 11 Feb 2020
The Practicality of Stochastic Optimization in Imaging Inverse Problems Junqi Tang K. Egiazarian Mohammad Golbabaee Mike Davies 27 30 0 22 Oct 2019
Semi-Cyclic Stochastic Gradient Descent Hubert Eichner Tomer Koren H. B. McMahan Nathan Srebro Kunal Talwar 24 106 0 23 Apr 2019
Memory-Sample Tradeoffs for Linear Regression with Small Error Vatsal Sharan Aaron Sidford Gregory Valiant 15 35 0 18 Apr 2019
Lower Bounds for Parallel and Randomized Convex Optimization Jelena Diakonikolas Cristóbal Guzmán 33 44 0 05 Nov 2018
Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization Eric Balkanski Yaron Singer 22 31 0 12 Aug 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 50 570 0 04 Jul 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Tight Query Complexity Lower Bounds for PCA via Finite Sample Deformed Wigner Law Max Simchowitz A. Alaoui Benjamin Recht 30 38 0 04 Apr 2018
Lower error bounds for the stochastic gradient descent optimization algorithm: Sharp convergence rates for slowly and fast decaying learning rates Arnulf Jentzen Philippe von Wurstemberger 73 31 0 22 Mar 2018
Leverage Score Sampling for Faster Accelerated Regression and ERM Naman Agarwal Sham Kakade Rahul Kidambi Y. Lee Praneeth Netrapalli Aaron Sidford 26 21 0 22 Nov 2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization Tomoya Murata Taiji Suzuki OffRL 33 28 0 01 Mar 2017
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 60 1,878 0 08 Oct 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method Lihua Lei Michael I. Jordan 29 96 0 12 Sep 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 15 577 0 18 Mar 2016
An optimal randomized incremental gradient method Guanghui Lan Yi Zhou 31 220 0 08 Jul 2015
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 43 261 0 10 Sep 2014