{"total":21,"rows":[{"id":"2112.02089","title":"Regularized Newton Method with Global $O(1/k^2)$ Convergence","created":"2021-12-03","cited_by_count":22,"area":null},{"id":"2209.07075","title":"Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients","created":"2022-09-15","cited_by_count":17,"area":null},{"id":"2303.07271","title":"Provably Convergent Plug-and-Play Quasi-Newton Methods","created":"2023-03-09","cited_by_count":15,"area":null},{"id":"2204.09266","title":"Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence","created":"2022-04-20","cited_by_count":14,"area":null},{"id":"2302.08580","title":"Online Learning Guided Curvature Approximation: A Quasi-Newton Method with Global Non-Asymptotic Superlinear Convergence","created":"2023-02-16","cited_by_count":11,"area":null},{"id":"2111.02708","title":"Quasi-Newton Methods for Saddle Point Problems and Beyond","created":"2021-11-04","cited_by_count":10,"area":null},{"id":"2306.02212","title":"Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization","created":"2023-06-03","cited_by_count":4,"area":null},{"id":"2307.13744","title":"mL-BFGS: A Momentum-based L-BFGS for Distributed Large-Scale Neural Network Optimization","created":"2023-07-25","cited_by_count":4,"area":null},{"id":"2305.13082","title":"Sketch-and-Project Meets Newton Method: Global $\\mathcal O(k^{-2})$ Convergence with Low-Rank Updates","created":"2023-05-22","cited_by_count":3,"area":null},{"id":"2408.00241","title":"Multiple Greedy Quasi-Newton Methods for Saddle Point Problems","created":"2024-08-01","cited_by_count":3,"area":null},{"id":"2505.23081","title":"Gradient Methods with Online Scaling Part I. Theoretical Foundations","created":"2025-05-29","cited_by_count":3,"area":null},{"id":"2402.02359","title":"Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates","created":"2024-02-04","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":"2408.08979","title":"Electroencephalogram Emotion Recognition via AUC Maximization","created":"2024-08-16","cited_by_count":2,"area":null},{"id":"2502.01076","title":"qNBO: quasi-Newton Meets Bilevel Optimization","created":"2025-02-03","cited_by_count":2,"area":null},{"id":"2305.17283","title":"Sharpened Lazy Incremental Quasi-Newton Method","created":"2023-05-26","cited_by_count":1,"area":null},{"id":"2309.01781","title":"Self-concordant smoothing in proximal quasi-Newton algorithms for large-scale convex composite optimization","created":"2023-09-04","cited_by_count":1,"area":null},{"id":"2306.15444","title":"Limited-Memory Greedy Quasi-Newton Method with Non-asymptotic Superlinear Convergence Rate","created":"2023-06-27","cited_by_count":0,"area":null},{"id":"2412.00059","title":"A Learn-to-Optimize Approach for Coordinate-Wise Step Sizes for Quasi-Newton Methods","created":"2024-11-25","cited_by_count":0,"area":null},{"id":"2508.19712","title":"Simple Stepsize for Quasi-Newton Methods with Global Convergence Guarantees","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2603.12838","title":"A New Kernel Regularity Condition for Distributed Mirror Descent: Broader Coverage and Simpler Analysis","created":"2026-03-13","cited_by_count":0,"area":null}],"next_cursor":null}