{"total":15,"rows":[{"id":"2109.05198","title":"Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information","created":"2021-09-11","cited_by_count":16,"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":"2207.08171","title":"SP2: A Second Order Stochastic Polyak Method","created":"2022-07-17","cited_by_count":13,"area":null},{"id":"2106.10708","title":"Memory Augmented Optimizers for Deep Learning","created":"2021-06-20","cited_by_count":5,"area":null},{"id":"2203.16340","title":"Optimization for Classical Machine Learning Problems on the GPU","created":"2022-03-30","cited_by_count":5,"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":"2106.05445","title":"Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach","created":"2021-06-10","cited_by_count":2,"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":"2410.19055","title":"Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms","created":"2024-10-24","cited_by_count":2,"area":null},{"id":"2103.04392","title":"A Retrospective Approximation Approach for Smooth Stochastic Optimization","created":"2021-03-07","cited_by_count":1,"area":null},{"id":"2205.09121","title":"On the efficiency of Stochastic Quasi-Newton Methods for Deep Learning","created":"2022-05-18","cited_by_count":1,"area":null},{"id":"2305.17283","title":"Sharpened Lazy Incremental Quasi-Newton Method","created":"2023-05-26","cited_by_count":1,"area":null},{"id":"2305.07484","title":"Online Learning Under A Separable Stochastic Approximation Framework","created":"2023-05-12","cited_by_count":0,"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":"2403.08378","title":"An Adaptive Cost-Sensitive Learning and Recursive Denoising Framework for Imbalanced SVM Classification","created":"2024-03-13","cited_by_count":0,"area":null}],"next_cursor":null}