{"total":119,"rows":[{"id":"2106.05203","title":"EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback","created":"2021-06-09","cited_by_count":133,"area":null},{"id":"2308.08165","title":"Stochastic Controlled Averaging for Federated Learning with Communication Compression","created":"2023-08-16","cited_by_count":101,"area":null},{"id":"2304.13972","title":"Convergence of Adam Under Relaxed Assumptions","created":"2023-04-27","cited_by_count":99,"area":null},{"id":"2102.07845","title":"MARINA: Faster Non-Convex Distributed Learning with Compression","created":"2021-02-15","cited_by_count":78,"area":null},{"id":"2202.05214","title":"Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo","created":"2022-02-10","cited_by_count":63,"area":null},{"id":"2302.01734","title":"Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies","created":"2023-02-03","cited_by_count":58,"area":null},{"id":"2103.15888","title":"The Complexity of Nonconvex-Strongly-Concave Minimax Optimization","created":"2021-03-29","cited_by_count":45,"area":null},{"id":"2506.04192","title":"Lions and Muons: Optimization via Stochastic Frank-Wolfe under Heavy-Tailed Noise","created":"2025-06-04","cited_by_count":41,"area":null},{"id":"2206.09888","title":"SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression","created":"2022-06-20","cited_by_count":34,"area":null},{"id":"2305.15155","title":"Momentum Provably Improves Error Feedback!","created":"2023-05-24","cited_by_count":31,"area":null},{"id":"2301.13139","title":"A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence","created":"2023-01-30","cited_by_count":30,"area":null},{"id":"2103.01447","title":"ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation","created":"2021-03-02","cited_by_count":29,"area":null},{"id":"2202.00998","title":"3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation","created":"2022-02-02","cited_by_count":27,"area":null},{"id":"2202.12396","title":"Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications","created":"2022-02-24","cited_by_count":27,"area":null},{"id":"2302.06763","title":"Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise","created":"2023-02-14","cited_by_count":27,"area":null},{"id":"2107.09461","title":"CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression","created":"2021-07-20","cited_by_count":23,"area":null},{"id":"2308.06058","title":"Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction","created":"2023-08-11","cited_by_count":23,"area":null},{"id":"2212.14370","title":"Can 5th Generation Local Training Methods Support Client Sampling? Yes!","created":"2022-12-29","cited_by_count":22,"area":null},{"id":"2303.00883","title":"Variance-reduced Clipping for Non-convex Optimization","created":"2023-03-02","cited_by_count":22,"area":null},{"id":"2108.04755","title":"FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning","created":"2021-08-10","cited_by_count":20,"area":null},{"id":"2203.09436","title":"Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions","created":"2022-03-17","cited_by_count":19,"area":null},{"id":"2410.16561","title":"Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise: Necessity, Sufficiency, and Acceleration","created":"2024-10-21","cited_by_count":18,"area":null},{"id":"2202.00308","title":"PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation","created":"2022-02-01","cited_by_count":17,"area":null},{"id":"2301.06428","title":"Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization","created":"2023-01-16","cited_by_count":17,"area":null},{"id":"2110.01165","title":"DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization","created":"2021-10-04","cited_by_count":16,"area":null},{"id":"2202.01268","title":"DASHA: Distributed Nonconvex Optimization with Communication Compression, Optimal Oracle Complexity, and No Client Synchronization","created":"2022-02-02","cited_by_count":16,"area":null},{"id":"2207.08540","title":"Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization","created":"2022-07-18","cited_by_count":16,"area":null},{"id":"2211.00188","title":"Adaptive Compression for Communication-Efficient Distributed Training","created":"2022-10-31","cited_by_count":16,"area":null},{"id":"2211.01851","title":"Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization","created":"2022-11-03","cited_by_count":15,"area":null},{"id":"2311.05645","title":"EControl: Fast Distributed Optimization with Compression and Error Control","created":"2023-11-06","cited_by_count":15,"area":null},{"id":"2112.13097","title":"Faster Rates for Compressed Federated Learning with Client-Variance Reduction","created":"2021-12-24","cited_by_count":14,"area":null},{"id":"2206.05891","title":"Anchor Sampling for Federated Learning with Partial Client Participation","created":"2022-06-13","cited_by_count":14,"area":null},{"id":"2205.08253","title":"Momentum-Based Policy Gradient with Second-Order Information","created":"2022-05-17","cited_by_count":13,"area":null},{"id":"2406.00489","title":"Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction","created":"2024-06-01","cited_by_count":13,"area":null},{"id":"2310.09804","title":"Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates","created":"2023-10-15","cited_by_count":12,"area":null},{"id":"2403.12338","title":"Stochastic Halpern iteration in normed spaces and applications to reinforcement learning","created":"2024-03-19","cited_by_count":12,"area":"deeprl"},{"id":"2305.18929","title":"Clip21: Error Feedback for Gradient Clipping","created":"2023-05-30","cited_by_count":11,"area":null},{"id":"2310.02987","title":"Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions","created":"2023-10-04","cited_by_count":11,"area":null},{"id":"2506.11214","title":"Complexity of normalized stochastic first-order methods with momentum under heavy-tailed noise","created":"2025-06-12","cited_by_count":11,"area":null},{"id":"2206.02275","title":"Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling","created":"2022-06-05","cited_by_count":10,"area":null},{"id":"2405.05630","title":"Policy Gradient with Active Importance Sampling","created":"2024-05-09","cited_by_count":10,"area":"deeprl"},{"id":"2103.11333","title":"ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method","created":"2021-03-21","cited_by_count":9,"area":null},{"id":"2111.10192","title":"An Expectation-Maximization Perspective on Federated Learning","created":"2021-11-19","cited_by_count":9,"area":null},{"id":"2212.05088","title":"Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization","created":"2022-12-09","cited_by_count":9,"area":null},{"id":"2110.03294","title":"EF21 with Bells & Whistles: Six Algorithmic Extensions of Modern Error Feedback","created":"2021-10-07","cited_by_count":8,"area":null},{"id":"2306.03240","title":"Improving Accelerated Federated Learning with Compression and Importance Sampling","created":"2023-06-05","cited_by_count":8,"area":null},{"id":"2111.13322","title":"Random-reshuffled SARAH does not need a full gradient computations","created":"2021-11-26","cited_by_count":7,"area":null},{"id":"2302.06032","title":"Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness","created":"2023-02-13","cited_by_count":7,"area":null},{"id":"2304.11737","title":"Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features","created":"2023-04-23","cited_by_count":7,"area":null},{"id":"2212.02387","title":"An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization","created":"2022-12-05","cited_by_count":6,"area":null},{"id":"2306.16484","title":"Towards a Better Theoretical Understanding of Independent Subnetwork Training","created":"2023-06-28","cited_by_count":6,"area":null},{"id":"2406.01959","title":"Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions","created":"2024-06-04","cited_by_count":6,"area":null},{"id":"2508.12327","title":"Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings","created":"2025-08-17","cited_by_count":6,"area":null},{"id":"2206.00285","title":"Stochastic Gradient Methods with Preconditioned Updates","created":"2022-06-01","cited_by_count":5,"area":null},{"id":"2208.10025","title":"Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization","created":"2022-08-22","cited_by_count":5,"area":null},{"id":"2209.14853","title":"META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Functions","created":"2022-09-29","cited_by_count":5,"area":null},{"id":"2307.15868","title":"Faster Stochastic Algorithms for Minimax Optimization under Polyak--{\\L}ojasiewicz Conditions","created":"2023-07-29","cited_by_count":5,"area":null},{"id":"2405.15545","title":"Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations","created":"2024-05-24","cited_by_count":5,"area":null},{"id":"2408.11084","title":"Multi-level Monte-Carlo Gradient Methods for Stochastic Optimization with Biased Oracles","created":"2024-08-20","cited_by_count":5,"area":null},{"id":"2604.16620","title":"Lower Bounds and Proximally Anchored SGD for Non-Convex Minimization Under Unbounded Variance","created":"2026-04-17","cited_by_count":5,"area":null},{"id":"2106.09663","title":"A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization","created":"2021-06-17","cited_by_count":4,"area":null},{"id":"2310.19059","title":"Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression","created":"2023-10-29","cited_by_count":4,"area":null},{"id":"2512.13123","title":"Stopping Rules for Stochastic Gradient Descent via Anytime-Valid Confidence Sequences","created":"2025-12-15","cited_by_count":4,"area":null},{"id":"2608.12043","title":"Direct Acceleration of Stochastic Root-Finding Without Variance Reduction and Regularization","created":"2026-08-12","cited_by_count":4,"area":null},{"id":"2301.00631","title":"Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization","created":"2023-01-02","cited_by_count":3,"area":null},{"id":"2303.04560","title":"Byzantine-Robust Loopless Stochastic Variance-Reduced Gradient","created":"2023-03-08","cited_by_count":3,"area":null},{"id":"2405.20127","title":"SPAM: Stochastic Proximal Point Method with Momentum Variance Reduction for Non-convex Cross-Device Federated Learning","created":"2024-05-30","cited_by_count":3,"area":null},{"id":"2505.02101","title":"Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization","created":"2025-05-04","cited_by_count":3,"area":null},{"id":"2509.02970","title":"Delayed Momentum Aggregation: Communication-efficient Byzantine-robust Federated Learning with Partial Participation","created":"2025-09-03","cited_by_count":3,"area":null},{"id":"2511.22331","title":"On the Condition Number Dependency in Bilevel Optimization","created":"2025-11-27","cited_by_count":3,"area":null},{"id":"2603.15576","title":"Unbiased and Biased Variance-Reduced Forward-Reflected-Backward Splitting Methods for Stochastic Composite Inclusions","created":"2026-03-16","cited_by_count":3,"area":null},{"id":"2604.10689","title":"Communication-Efficient Gluon in Federated Learning","created":"2026-04-12","cited_by_count":3,"area":null},{"id":"2206.00529","title":"Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top","created":"2022-06-01","cited_by_count":2,"area":null},{"id":"2307.07113","title":"Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems","created":"2023-07-14","cited_by_count":2,"area":null},{"id":"2401.03489","title":"Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence","created":"2024-01-07","cited_by_count":2,"area":"deeprl"},{"id":"2401.15890","title":"Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems","created":"2024-01-29","cited_by_count":2,"area":null},{"id":"2402.02569","title":"On the Complexity of Finite-Sum Smooth Optimization under the Polyak-{\\L}ojasiewicz Condition","created":"2024-02-04","cited_by_count":2,"area":null},{"id":"2402.06033","title":"An Inexact Halpern Iteration with Application to Distributionally Robust Optimization","created":"2024-02-08","cited_by_count":2,"area":null},{"id":"2403.06677","title":"Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction","created":"2024-03-11","cited_by_count":2,"area":null},{"id":"2409.14280","title":"Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning","created":"2024-09-22","cited_by_count":2,"area":null},{"id":"2110.13144","title":"Faster Perturbed Stochastic Gradient Methods for Finding Local Minima","created":"2021-10-25","cited_by_count":1,"area":null},{"id":"2208.08425","title":"SYNTHESIS: A Semi-Asynchronous Path-Integrated Stochastic Gradient Method for Distributed Learning in Computing Clusters","created":"2022-08-17","cited_by_count":1,"area":null},{"id":"2305.15264","title":"Error Feedback Shines when Features are Rare","created":"2023-05-24","cited_by_count":1,"area":null},{"id":"2401.12508","title":"On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization","created":"2024-01-23","cited_by_count":1,"area":"deeprl"},{"id":"2403.15244","title":"A Stochastic Quasi-Newton Method for Non-convex Optimization with Non-uniform Smoothness","created":"2024-03-22","cited_by_count":1,"area":null},{"id":"2405.17761","title":"Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient","created":"2024-05-28","cited_by_count":1,"area":null},{"id":"2409.08640","title":"Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering","created":"2024-09-13","cited_by_count":1,"area":null},{"id":"2412.12987","title":"Stochastic interior-point methods for smooth conic optimization with applications","created":"2024-12-17","cited_by_count":1,"area":null},{"id":"2502.21099","title":"Adaptive Lipschitz-Free Proximal Gradient Methods for Stochastic Composite Nonconvex Optimization","created":"2025-02-28","cited_by_count":1,"area":null},{"id":"2512.05327","title":"Non-Convex Federated Optimization under Cost-Aware Client Selection","created":"2025-12-05","cited_by_count":1,"area":null},{"id":"2605.30573","title":"Zeroth-Order Non-Log-Concave Sampling with Variance Reduction and Applications to Inverse Problems","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2607.21975","title":"On the Convergence of Stochastic Low-Rank Adaptation","created":"2026-07-24","cited_by_count":1,"area":null},{"id":"2608.15966","title":"A Banach-Space Theory of Markovian Halpern Iteration for Non-Expansive Maps","created":"2026-08-16","cited_by_count":1,"area":null},{"id":"2609.08133","title":"Sparse Data Augmentation for Optimization with Provable Guarantees","created":"2026-09-08","cited_by_count":1,"area":null},{"id":"2610.03165","title":"Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds","created":"2026-10-02","cited_by_count":1,"area":"deeprl"},{"id":"2208.00502","title":"Formal guarantees for heuristic optimization algorithms used in machine learning","created":"2022-07-31","cited_by_count":0,"area":null},{"id":"2209.00361","title":"Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning","created":"2022-09-01","cited_by_count":0,"area":null},{"id":"2210.05994","title":"SARAH-based Variance-reduced Algorithm for Stochastic Finite-sum Cocoercive Variational Inequalities","created":"2022-10-12","cited_by_count":0,"area":null},{"id":"2211.12685","title":"Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems","created":"2022-11-23","cited_by_count":0,"area":null},{"id":"2304.11788","title":"Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems?","created":"2023-04-24","cited_by_count":0,"area":null}],"next_cursor":"100"}