{"list":"other","total":58,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1602.05629","title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","created":"2016-02-17","cited_by_count":7669},{"id":"1812.06127","title":"Federated Optimization in Heterogeneous Networks","created":"2018-12-14","cited_by_count":2987},{"id":"1704.00028","title":"Improved Training of Wasserstein GANs","created":"2017-03-31","cited_by_count":2235},{"id":"2003.00295","title":"Adaptive Federated Optimization","created":"2020-02-29","cited_by_count":1046},{"id":"1811.03962","title":"A Convergence Theory for Deep Learning via Over-Parameterization","created":"2018-11-09","cited_by_count":787},{"id":"1905.10018","title":"Momentum-Based Variance Reduction in Non-Convex SGD","created":"2019-05-24","cited_by_count":306},{"id":"1807.01695","title":"SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator","created":"2018-07-04","cited_by_count":287},{"id":"1906.00331","title":"On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems","created":"2019-06-02","cited_by_count":270},{"id":"1803.06523","title":"Stochastic model-based minimization of weakly convex functions","created":"2018-03-17","cited_by_count":159},{"id":"2008.03606","title":"Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning","created":"2020-08-08","cited_by_count":154},{"id":"1902.08297","title":"Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods","created":"2019-02-21","cited_by_count":148},{"id":"2102.12660","title":"Distributionally Robust Federated Averaging","created":"2021-02-25","cited_by_count":104},{"id":"2006.08907","title":"Robust Federated Learning: The Case of Affine Distribution Shifts","created":"2020-06-16","cited_by_count":102},{"id":"1710.08402","title":"Stability and Generalization of Learning Algorithms that Converge to Global Optima","created":"2017-10-23","cited_by_count":100},{"id":"2011.00364","title":"Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization","created":"2020-10-31","cited_by_count":96},{"id":"2006.07228","title":"FedGAN: Federated Generative Adversarial Networks for Distributed Data","created":"2020-06-12","cited_by_count":90},{"id":"2001.03724","title":"Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems","created":"2020-01-11","cited_by_count":77},{"id":"1907.01543","title":"Efficient Algorithms for Smooth Minimax Optimization","created":"2019-07-02","cited_by_count":76},{"id":"1908.10831","title":"Stochastic AUC Maximization with Deep Neural Networks","created":"2019-08-28","cited_by_count":61},{"id":"2205.02215","title":"FedNest: Federated Bilevel, Minimax, and Compositional Optimization","created":"2022-05-04","cited_by_count":60},{"id":"2112.05604","title":"Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity","created":"2021-12-10","cited_by_count":49},{"id":"1910.12999","title":"A Decentralized Parallel Algorithm for Training Generative Adversarial Nets","created":"2019-10-28","cited_by_count":43},{"id":"2106.10435","title":"STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning","created":"2021-06-19","cited_by_count":43},{"id":"2008.08170","title":"Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization","created":"2020-08-18","cited_by_count":40},{"id":"2102.13152","title":"Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency","created":"2021-02-25","cited_by_count":40},{"id":"2203.04850","title":"Federated Minimax Optimization: Improved Convergence Analyses and Algorithms","created":"2022-03-09","cited_by_count":37},{"id":"2307.16212","title":"Robust Multi-Agent Reinforcement Learning with State Uncertainty","created":"2023-07-30","cited_by_count":36},{"id":"2212.00974","title":"Faster Adaptive Federated Learning","created":"2022-12-02","cited_by_count":35},{"id":"1906.03563","title":"Adversarial Attack Generation Empowered by Min-Max Optimization","created":"2019-06-09","cited_by_count":32},{"id":"1905.13433","title":"An accelerated inexact proximal point method for solving nonconvex-concave min-max problems","created":"2019-05-31","cited_by_count":30},{"id":"2005.02426","title":"Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks","created":"2020-05-05","cited_by_count":27},{"id":"2106.08315","title":"Decentralized Local Stochastic Extra-Gradient for Variational Inequalities","created":"2021-06-15","cited_by_count":25},{"id":"2205.15084","title":"SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems","created":"2022-05-30","cited_by_count":23},{"id":"2212.02705","title":"What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?","created":"2022-12-06","cited_by_count":22},{"id":"2102.04635","title":"Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity","created":"2021-02-09","cited_by_count":21},{"id":"2212.04983","title":"Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks","created":"2022-12-09","cited_by_count":21},{"id":"1902.00618","title":"What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?","created":"2019-02-02","cited_by_count":20},{"id":"2102.06333","title":"Efficient Algorithms for Federated Saddle Point Optimization","created":"2021-02-12","cited_by_count":20},{"id":"2302.10418","title":"MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization","created":"2023-02-21","cited_by_count":20},{"id":"2010.06097","title":"Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds","created":"2020-10-13","cited_by_count":16},{"id":"2206.00743","title":"Nest Your Adaptive Algorithm for Parameter-Agnostic Nonconvex Minimax Optimization","created":"2022-06-01","cited_by_count":16},{"id":"2206.11225","title":"RetrievalGuard: Provably Robust 1-Nearest Neighbor Image Retrieval","created":"2022-06-17","cited_by_count":15},{"id":"2208.06058","title":"An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification","created":"2022-08-11","cited_by_count":14},{"id":"2104.14840","title":"Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator","created":"2021-04-30","cited_by_count":13},{"id":"2106.16101","title":"AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization","created":"2021-06-30","cited_by_count":13},{"id":"2210.14396","title":"FeDXL: Provable Federated Learning for Deep X-Risk Optimization","created":"2022-10-26","cited_by_count":11},{"id":"2202.11592","title":"A Law of Robustness beyond Isoperimetry","created":"2022-02-23","cited_by_count":9},{"id":"2206.01132","title":"A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning","created":"2022-06-02","cited_by_count":9},{"id":"2302.04249","title":"Federated Minimax Optimization with Client Heterogeneity","created":"2023-02-08","cited_by_count":8},{"id":"2210.09382","title":"Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems","created":"2022-10-17","cited_by_count":7},{"id":"2302.03825","title":"Decentralized Riemannian Algorithm for Nonconvex Minimax Problems","created":"2023-02-08","cited_by_count":7},{"id":"2306.00187","title":"AccMER: Accelerating Multi-Agent Experience Replay with Cache Locality-aware Prioritization","created":"2023-05-31","cited_by_count":7},{"id":"2307.16228","title":"Robust Electric Vehicle Balancing of Autonomous Mobility-On-Demand System: A Multi-Agent Reinforcement Learning Approach","created":"2023-07-30","cited_by_count":6},{"id":"2303.02532","title":"PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities","created":"2023-03-05","cited_by_count":5},{"id":"2307.15868","title":"Faster Stochastic Algorithms for Minimax Optimization under Polyak--{\\L}ojasiewicz Conditions","created":"2023-07-29","cited_by_count":5},{"id":"2304.10902","title":"Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems","created":"2023-04-21","cited_by_count":4},{"id":"2310.02524","title":"Federated Conditional Stochastic Optimization","created":"2023-10-04","cited_by_count":4}],"next_cursor":null}