{"total":47,"rows":[{"id":"2107.07467","title":"Only Train Once: A One-Shot Neural Network Training And Pruning Framework","created":"2021-07-15","cited_by_count":70,"area":null},{"id":"2102.04761","title":"Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data","created":"2021-02-09","cited_by_count":69,"area":null},{"id":"2411.10438","title":"MARS: Unleashing the Power of Variance Reduction for Training Large Models","created":"2024-11-15","cited_by_count":64,"area":null},{"id":"2306.01244","title":"Towards Sustainable Learning: Coresets for Data-efficient Deep Learning","created":"2023-06-02","cited_by_count":44,"area":null},{"id":"2108.09875","title":"Anarchic Federated Learning","created":"2021-08-23","cited_by_count":42,"area":null},{"id":"2203.10144","title":"Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation","created":"2022-03-18","cited_by_count":42,"area":null},{"id":"2303.00883","title":"Variance-reduced Clipping for Non-convex Optimization","created":"2023-03-02","cited_by_count":22,"area":null},{"id":"2103.03265","title":"Better SGD using Second-order Momentum","created":"2021-03-04","cited_by_count":15,"area":null},{"id":"2110.06256","title":"Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective","created":"2021-10-12","cited_by_count":15,"area":null},{"id":"2103.02062","title":"Variance Reduced Training with Stratified Sampling for Forecasting Models","created":"2021-03-02","cited_by_count":14,"area":null},{"id":"2310.11428","title":"Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression","created":"2023-10-17","cited_by_count":14,"area":null},{"id":"2102.09645","title":"SVRG Meets AdaGrad: Painless Variance Reduction","created":"2021-02-18","cited_by_count":13,"area":null},{"id":"2106.11257","title":"Secure Distributed Training at Scale","created":"2021-06-21","cited_by_count":12,"area":null},{"id":"2404.08447","title":"Federated Optimization with Doubly Regularized Drift Correction","created":"2024-04-12","cited_by_count":10,"area":null},{"id":"2405.14402","title":"Exact Gauss-Newton Optimization for Training Deep Neural Networks","created":"2024-05-23","cited_by_count":10,"area":null},{"id":"2510.21800","title":"MARS-M: When Variance Reduction Meets Matrices","created":"2025-10-20","cited_by_count":10,"area":null},{"id":"2102.03970","title":"Coordinating Momenta for Cross-silo Federated Learning","created":"2021-02-08","cited_by_count":9,"area":null},{"id":"2212.02191","title":"On the effectiveness of partial variance reduction in federated learning with heterogeneous data","created":"2022-12-05","cited_by_count":9,"area":null},{"id":"2302.07071","title":"Statistically Optimal Force Aggregation for Coarse-Graining Molecular Dynamics","created":"2023-02-14","cited_by_count":9,"area":null},{"id":"2201.03789","title":"Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits","created":"2022-01-11","cited_by_count":8,"area":null},{"id":"2310.15165","title":"Handling Data Heterogeneity via Architectural Design for Federated Visual Recognition","created":"2023-10-23","cited_by_count":8,"area":null},{"id":"2103.12293","title":"Stochastic Reweighted Gradient Descent","created":"2021-03-23","cited_by_count":7,"area":null},{"id":"2112.02612","title":"Training Structured Neural Networks Through Manifold Identification and Variance Reduction","created":"2021-12-05","cited_by_count":7,"area":null},{"id":"2306.14522","title":"Nonconvex Stochastic Bregman Proximal Gradient Method with Application to Deep Learning","created":"2023-06-26","cited_by_count":7,"area":null},{"id":"2311.05589","title":"A Coefficient Makes SVRG Effective","created":"2023-11-09","cited_by_count":7,"area":null},{"id":"2107.06534","title":"Zeroth and First Order Stochastic Frank-Wolfe Algorithms for Constrained Optimization","created":"2021-07-14","cited_by_count":6,"area":null},{"id":"2311.18578","title":"Communication-Efficient Heterogeneous Federated Learning with Generalized Heavy-Ball Momentum","created":"2023-11-30","cited_by_count":3,"area":null},{"id":"2505.07614","title":"Bant: Byzantine Antidote via Trial Function and Trust Scores","created":"2025-05-12","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":"2111.11828","title":"Variance Reduction in Deep Learning: More Momentum is All You Need","created":"2021-11-23","cited_by_count":2,"area":null},{"id":"2202.09052","title":"Tackling benign nonconvexity with smoothing and stochastic gradients","created":"2022-02-18","cited_by_count":2,"area":null},{"id":"2408.03199","title":"Convergence Conditions for Stochastic Line Search Based Optimization of Over-parametrized Models","created":"2024-08-06","cited_by_count":2,"area":null},{"id":"2511.05187","title":"Gradient Prediction with Control Variates in the Cheap-Forward Regime","created":"2025-11-07","cited_by_count":2,"area":null},{"id":"2304.05127","title":"Balancing Privacy and Performance for Private Federated Learning Algorithms","created":"2023-04-11","cited_by_count":1,"area":null},{"id":"2407.18821","title":"Deep Companion Learning: Enhancing Generalization Through Historical Consistency","created":"2024-07-26","cited_by_count":1,"area":null},{"id":"2411.07102","title":"Effectively Leveraging Momentum Terms in Stochastic Line Search Frameworks for Fast Optimization of Finite-Sum Problems","created":"2024-11-11","cited_by_count":1,"area":null},{"id":"2509.02937","title":"Faster Gradient Methods for Highly-Smooth Stochastic Bilevel Optimization","created":"2025-09-03","cited_by_count":1,"area":null},{"id":"2105.03527","title":"Scalable Projection-Free Optimization","created":"2021-05-07","cited_by_count":0,"area":null},{"id":"2105.13464","title":"Training With Data Dependent Dynamic Learning Rates","created":"2021-05-27","cited_by_count":0,"area":null},{"id":"2306.15848","title":"Ordering for Non-Replacement SGD","created":"2023-06-28","cited_by_count":0,"area":null},{"id":"2404.02378","title":"Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation","created":"2024-04-03","cited_by_count":0,"area":null},{"id":"2405.20623","title":"Sparse-ProxSkip: Accelerated Sparse-to-Sparse Training in Federated Learning","created":"2024-05-31","cited_by_count":0,"area":null},{"id":"2503.12454","title":"Convergence Analysis of alpha-SVRG under Strong Convexity","created":"2025-03-16","cited_by_count":0,"area":null},{"id":"2512.01930","title":"SVRG and Beyond via Posterior Correction","created":"2025-12-01","cited_by_count":0,"area":null},{"id":"2601.08614","title":"Accelerated Methods with Complexity Separation Under Data Similarity for Federated Learning Problems","created":"2026-01-13","cited_by_count":0,"area":null},{"id":"2605.08871","title":"Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2606.21528","title":"Accelerated and Stable Convergence with Anchored Generalized Optimistic Method","created":"2026-06-19","cited_by_count":0,"area":null}],"next_cursor":null}