Optimization Methods for Large-Scale Machine Learning

15 June 2016

Papers citing "Optimization Methods for Large-Scale Machine Learning"

50 / 1,407 papers shown

Title
MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately) Johanni Brea Flavio Martinelli Berfin Simsek W. Gerstner 31 3 0 25 Jan 2023
Deterministic Online Classification: Non-iteratively Reweighted Recursive Least-Squares for Binary Class Rebalancing Se-In Jang 11 0 0 22 Jan 2023
A Stochastic Proximal Polyak Step Size Fabian Schaipp Robert Mansel Gower M. Ulbrich 19 12 0 12 Jan 2023
Federated Learning under Heterogeneous and Correlated Client Availability Angelo Rodio Francescomaria Faticanti Othmane Marfoq Giovanni Neglia Emilio Leonardi FedML 18 27 0 11 Jan 2023
Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation Xiao-Tong Yuan P. Li 36 2 0 09 Jan 2023
Federated Learning for Data Streams Othmane Marfoq Giovanni Neglia Laetitia Kameni Richard Vidal FedML 37 12 0 04 Jan 2023
CC-FedAvg: Computationally Customized Federated Averaging Hao Zhang Tingting Wu Siyao Cheng Jie Liu FedML 18 5 0 28 Dec 2022
Variance Reduction for Score Functions Using Optimal Baselines Ronan L. Keane H. Gao 21 0 0 27 Dec 2022
Deep Unfolding-based Weighted Averaging for Federated Learning in Heterogeneous Environments Ayano Nakai-Kasai T. Wadayama FedML 27 0 0 23 Dec 2022
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis Quoc Tran-Dinh Marten van Dijk 34 0 0 19 Dec 2022
Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent Richard Archibald F. Bao Yanzhao Cao Hui‐Jie Sun 52 2 0 17 Dec 2022
Scheduling and Aggregation Design for Asynchronous Federated Learning over Wireless Networks Chung-Hsuan Hu Zheng Chen Erik G. Larsson 27 64 0 14 Dec 2022
Learning useful representations for shifting tasks and distributions Jianyu Zhang Léon Bottou OOD 34 13 0 14 Dec 2022
Low-Variance Forward Gradients using Direct Feedback Alignment and Momentum Florian Bacho Dominique F. Chu 21 8 0 14 Dec 2022
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle Points Mayank Baranwal Param Budhraja V. Raj A. Hota 33 2 0 07 Dec 2022
Distributed Stochastic Gradient Descent with Cost-Sensitive and Strategic Agents Abdullah Basar Akbay C. Tepedelenlioğlu FedML 15 0 0 05 Dec 2022
Convergence of ease-controlled Random Reshuffling gradient Algorithms under Lipschitz smoothness R. Seccia Corrado Coppola G. Liuzzi L. Palagi 26 2 0 04 Dec 2022
Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints Jianyi Yang Shaolei Ren 20 2 0 03 Dec 2022
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning Shiqi He Qifan Yan Feijie Wu Lanjun Wang Mathias Lécuyer Ivan Beschastnikh FedML 42 7 0 03 Dec 2022
Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems Yuchen Fang Sen Na Michael W. Mahoney Mladen Kolar 13 22 0 29 Nov 2022
Impact of Redundancy on Resilience in Distributed Optimization and Learning Shuo Liu Nirupam Gupta Nitin H. Vaidya 34 2 0 16 Nov 2022
General Intelligence Requires Rethinking Exploration Minqi Jiang Tim Rocktaschel Edward Grefenstette LRM 29 18 0 15 Nov 2022
Adaptive Federated Minimax Optimization with Lower Complexities Feihu Huang Xinrui Wang Junyi Li Songcan Chen FedML 13 5 0 14 Nov 2022
Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design Yuchang Sun Jiawei Shao Yuyi Mao Songze Li Jun Zhang FedML 24 8 0 08 Nov 2022
Neural PDE Solvers for Irregular Domains Biswajit Khara Ethan Herron Zhanhong Jiang Aditya Balu Chih-Hsuan Yang ... Anushrut Jignasu S. Sarkar C. Hegde A. Krishnamurthy Baskar Ganapathysubramanian AI4CE 24 7 0 07 Nov 2022
Accelerating Parallel Stochastic Gradient Descent via Non-blocking Mini-batches Haoze He Parijat Dube 6 3 0 02 Nov 2022
RCD-SGD: Resource-Constrained Distributed SGD in Heterogeneous Environment via Submodular Partitioning Haoze He Parijat Dube 15 1 0 02 Nov 2022
Convergence analysis of a quasi-Monte Carlo-based deep learning algorithm for solving partial differential equations Fengjiang Fu Xiaoqun Wang 29 2 0 28 Oct 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 27 0 0 28 Oct 2022
NeuralSearchX: Serving a Multi-billion-parameter Reranker for Multilingual Metasearch at a Low Cost Thales Sales Almeida Thiago Laitz Joao Seródio L. Bonifacio R. Lotufo Rodrigo Nogueira 22 4 0 26 Oct 2022
Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity Xuxing Chen Minhui Huang Shiqian Ma Krishnakumar Balasubramanian 27 25 0 23 Oct 2022
Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach H. Fernando Han Shen Miao Liu Subhajit Chaudhury K. Murugesan Tianyi Chen 36 8 0 23 Oct 2022
A note on diffusion limits for stochastic gradient descent Alberto Lanconelli Christopher S. A. Lauria DiffM 22 1 0 20 Oct 2022
PAC-Bayesian Learning of Optimization Algorithms Michael Sucker Peter Ochs 27 4 0 20 Oct 2022
Block-wise Primal-dual Algorithms for Large-scale Doubly Penalized ANOVA Modeling Penghui Fu Z. Tan 21 5 0 20 Oct 2022
Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability Zhao Song Yitan Wang Zheng Yu Licheng Zhang FedML 23 28 0 15 Oct 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 29 11 0 14 Oct 2022
Joint control variate for faster black-box variational inference Xi Wang Tomas Geffner Justin Domke BDL DRL 19 0 0 13 Oct 2022
SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities Aleksandr Beznosikov Alexander Gasnikov 40 2 0 12 Oct 2022
Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach Peng Mi Li Shen Tianhe Ren Yiyi Zhou Xiaoshuai Sun Rongrong Ji Dacheng Tao AAML 38 69 0 11 Oct 2022
Robust Graph Structure Learning via Multiple Statistical Tests Yaohua Wang Fangyi Zhang Ming Lin Senzhang Wang Xiuyu Sun Rong Jin 34 1 0 08 Oct 2022
Scaling up Stochastic Gradient Descent for Non-convex Optimisation S. Mohamad H. Alamri A. Bouchachia 50 3 0 06 Oct 2022
Over-the-Air Federated Learning with Privacy Protection via Correlated Additive Perturbations Jialing Liao Zheng Chen Erik G. Larsson 25 12 0 05 Oct 2022
Taming Fat-Tailed ("Heavier-Tailed'' with Potentially Infinite Variance) Noise in Federated Learning Haibo Yang Pei-Yuan Qiu Jia Liu FedML 35 12 0 03 Oct 2022
Stochastic optimization on matrices and a graphon McKean-Vlasov limit Zaïd Harchaoui Sewoong Oh Soumik Pal Raghav Somani Raghavendra Tripathi 36 2 0 02 Oct 2022
Downlink Compression Improves TopK Sparsification William Zou H. Sterck Jun Liu 21 0 0 30 Sep 2022
Benchmarking Learning Efficiency in Deep Reservoir Computing Hugo Cisneros Josef Sivic Tomáš Mikolov 14 2 0 29 Sep 2022
FG-UAP: Feature-Gathering Universal Adversarial Perturbation Zhixing Ye Xinwen Cheng X. Huang AAML 74 10 0 27 Sep 2022
Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descent Yicheng Chen Rick S. Blum Brian M. Sadler FedML 28 4 0 24 Sep 2022
Robust Collaborative Learning with Linear Gradient Overhead Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot John Stephan FedML 14 15 0 22 Sep 2022