{"total":30,"rows":[{"id":"2209.05364","title":"If Influence Functions are the Answer, Then What is the Question?","created":"2022-09-12","cited_by_count":144,"area":null},{"id":"2110.02796","title":"An Unconstrained Layer-Peeled Perspective on Neural Collapse","created":"2021-10-06","cited_by_count":87,"area":null},{"id":"2302.01186","title":"The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing","created":"2023-02-02","cited_by_count":33,"area":null},{"id":"2212.14032","title":"On Implicit Bias in Overparameterized Bilevel Optimization","created":"2022-12-28","cited_by_count":30,"area":null},{"id":"2104.11044","title":"Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes","created":"2021-04-22","cited_by_count":28,"area":null},{"id":"2112.03215","title":"Multi-scale Feature Learning Dynamics: Insights for Double Descent","created":"2021-12-06","cited_by_count":24,"area":null},{"id":"2302.03764","title":"Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions","created":"2023-02-07","cited_by_count":17,"area":null},{"id":"2507.12224","title":"Optimizers Qualitatively Alter Solutions And We Should Leverage This","created":"2025-07-16","cited_by_count":17,"area":null},{"id":"2312.12226","title":"On the Parameterization of Second-Order Optimization Effective Towards the Infinite Width","created":"2023-12-19","cited_by_count":15,"area":null},{"id":"2502.05075","title":"Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension","created":"2025-02-07","cited_by_count":12,"area":null},{"id":"2205.07331","title":"Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent","created":"2022-05-15","cited_by_count":11,"area":null},{"id":"2304.01552","title":"Meta-Learning with a Geometry-Adaptive Preconditioner","created":"2023-04-04","cited_by_count":11,"area":null},{"id":"2307.14531","title":"Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum","created":"2023-07-26","cited_by_count":9,"area":null},{"id":"2308.06703","title":"Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods","created":"2023-08-13","cited_by_count":8,"area":null},{"id":"2206.15143","title":"Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning","created":"2022-06-30","cited_by_count":7,"area":null},{"id":"2111.11542","title":"Depth Without the Magic: Inductive Bias of Natural Gradient Descent","created":"2021-11-22","cited_by_count":5,"area":null},{"id":"2306.00342","title":"Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks","created":"2023-06-01","cited_by_count":4,"area":null},{"id":"2110.11258","title":"On Optimal Interpolation In Linear Regression","created":"2021-10-21","cited_by_count":3,"area":null},{"id":"2403.08585","title":"Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems","created":"2024-03-13","cited_by_count":3,"area":null},{"id":"2502.18153","title":"SASSHA: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation","created":"2025-02-25","cited_by_count":3,"area":null},{"id":"2511.19716","title":"Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability","created":"2025-11-24","cited_by_count":2,"area":null},{"id":"2412.15483","title":"Task-Specific Preconditioner for Cross-Domain Few-Shot Learning","created":"2024-12-20","cited_by_count":1,"area":null},{"id":"2506.17187","title":"Optimal Implicit Bias in Linear Regression","created":"2025-06-20","cited_by_count":1,"area":null},{"id":"2601.03162","title":"On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime","created":"2026-01-06","cited_by_count":1,"area":null},{"id":"2606.16301","title":"One-Step Generalization Ratio Guided Optimization for Domain Generalization","created":"2026-06-15","cited_by_count":1,"area":null},{"id":"2201.08311","title":"Accelerated Gradient Flow: Risk, Stability, and Implicit Regularization","created":"2022-01-20","cited_by_count":0,"area":null},{"id":"2509.25637","title":"How Does Preconditioning Guide Feature Learning in Deep Neural Networks?","created":"2025-09-30","cited_by_count":0,"area":null},{"id":"2511.03972","title":"Non-Asymptotic Optimization and Generalization Bounds for Stochastic Gauss-Newton in Overparameterized Models","created":"2025-11-06","cited_by_count":0,"area":null},{"id":"2602.23219","title":"Takeuchi's Information Criteria as Generalization Measures for DNNs Close to NTK Regime","created":"2026-02-26","cited_by_count":0,"area":null},{"id":"2610.16845","title":"Feature Normalization under Finite Training Budgets","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}