{"total":38,"rows":[{"id":"2402.03293","title":"Flora: Low-Rank Adapters Are Secretly Gradient Compressors","created":"2024-02-05","cited_by_count":108,"area":null},{"id":"2210.09221","title":"Vision Transformers provably learn spatial structure","created":"2022-10-13","cited_by_count":93,"area":null},{"id":"2303.15725","title":"Solving Regularized Exp, Cosh and Sinh Regression Problems","created":"2023-03-28","cited_by_count":44,"area":null},{"id":"2306.04949","title":"Robust Learning with Progressive Data Expansion Against Spurious Correlation","created":"2023-06-08","cited_by_count":39,"area":null},{"id":"2305.15155","title":"Momentum Provably Improves Error Feedback!","created":"2023-05-24","cited_by_count":31,"area":null},{"id":"2310.07269","title":"Why Does Sharpness-Aware Minimization Generalize Better Than SGD?","created":"2023-10-11","cited_by_count":28,"area":null},{"id":"2302.00849","title":"Implicit regularization in Heavy-ball momentum accelerated stochastic gradient descent","created":"2023-02-02","cited_by_count":25,"area":null},{"id":"2303.08433","title":"The Benefits of Mixup for Feature Learning","created":"2023-03-15","cited_by_count":19,"area":null},{"id":"2307.15196","title":"The Marginal Value of Momentum for Small Learning Rate SGD","created":"2023-07-27","cited_by_count":18,"area":null},{"id":"2604.14108","title":"Momentum Further Constrains Sharpness at the Edge of Stochastic Stability","created":"2026-04-15","cited_by_count":10,"area":null},{"id":"2403.02967","title":"Non-convex Stochastic Composite Optimization with Polyak Momentum","created":"2024-03-05","cited_by_count":9,"area":null},{"id":"2403.05293","title":"Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks","created":"2024-03-08","cited_by_count":9,"area":null},{"id":"2410.23495","title":"DASH: Warm-Starting Neural Network Training in Stationary Settings without Loss of Plasticity","created":"2024-10-30","cited_by_count":7,"area":null},{"id":"2401.11600","title":"Understanding the Generalization Benefits of Late Learning Rate Decay","created":"2024-01-21","cited_by_count":6,"area":null},{"id":"2306.01271","title":"On the Clean Generalization and Robust Overfitting in Adversarial Training from Two Theoretical Views: Representation Complexity and Training Dynamics","created":"2023-06-02","cited_by_count":5,"area":null},{"id":"2407.05594","title":"SLIM: Spuriousness Mitigation with Minimal Human Annotations","created":"2024-07-08","cited_by_count":5,"area":null},{"id":"2512.23422","title":"Entropy-Guided Token Dropout: Training Autoregressive Language Models with Limited Domain Data","created":"2025-12-29","cited_by_count":5,"area":null},{"id":"2410.13743","title":"Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness: Theories and Applications","created":"2024-10-17","cited_by_count":4,"area":null},{"id":"2410.23672","title":"Provable Benefit of Cutout and CutMix for Feature Learning","created":"2024-10-31","cited_by_count":4,"area":null},{"id":"2505.18909","title":"On the Role of Label Noise in the Feature Learning Process","created":"2025-05-25","cited_by_count":4,"area":null},{"id":"2510.17526","title":"How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?","created":"2025-10-20","cited_by_count":4,"area":null},{"id":"2210.06819","title":"Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence","created":"2022-10-13","cited_by_count":3,"area":null},{"id":"2311.15051","title":"Gradient Descent with Polyak's Momentum Finds Flatter Minima via Large Catapults","created":"2023-11-25","cited_by_count":3,"area":null},{"id":"2404.17768","title":"Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization","created":"2024-04-27","cited_by_count":3,"area":null},{"id":"2511.18006","title":"Understanding Private Learning From Feature Perspective","created":"2025-11-22","cited_by_count":3,"area":null},{"id":"2403.07379","title":"Hallmarks of Optimization Trajectories in Neural Networks: Directional Exploration and Redundancy","created":"2024-03-12","cited_by_count":2,"area":null},{"id":"2405.18222","title":"From Learning to Optimize to Learning Optimization Algorithms","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2409.18685","title":"Understanding the Benefits of SimCLR Pre-Training in Two-Layer Convolutional Neural Networks","created":"2024-09-27","cited_by_count":2,"area":null},{"id":"2502.11893","title":"Rethinking Benign Overfitting in Two-Layer Neural Networks","created":"2025-02-17","cited_by_count":2,"area":null},{"id":"2606.17526","title":"MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization","created":"2026-06-16","cited_by_count":2,"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":"2510.04988","title":"Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization","created":"2025-10-06","cited_by_count":1,"area":null},{"id":"2602.02767","title":"Provable Effects of Data Replay in Continual Learning: A Feature Learning Perspective","created":"2026-02-02","cited_by_count":1,"area":null},{"id":"2603.04881","title":"Differential Privacy in Two-Layer Networks: How DP-SGD Harms Fairness and Robustness","created":"2026-03-05","cited_by_count":1,"area":null},{"id":"2603.15492","title":"Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold","created":"2026-03-16","cited_by_count":1,"area":null},{"id":"2411.16303","title":"Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization","created":"2024-11-25","cited_by_count":0,"area":null},{"id":"2412.14488","title":"A stochastic first-order method with multi-extrapolated momentum for highly smooth unconstrained optimization","created":"2024-12-19","cited_by_count":0,"area":null},{"id":"2605.29635","title":"MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-Regularized Optimization","created":"2026-05-28","cited_by_count":0,"area":null}],"next_cursor":null}