Sub-Sampled Newton Methods II: Local Convergence Rates

18 January 2016

Papers citing "Sub-Sampled Newton Methods II: Local Convergence Rates"

16 / 16 papers shown

Title
SCORE: Approximating Curvature Information under Self-Concordant Regularization Adeyemi Damilare Adeoye Alberto Bemporad 20 4 0 14 Dec 2021
Iterative Teaching by Label Synthesis Weiyang Liu Zhen Liu Hanchen Wang Liam Paull Bernhard Schölkopf Adrian Weller 48 16 0 27 Oct 2021
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms A. Camuto George Deligiannidis Murat A. Erdogdu Mert Gurbuzbalaban Umut cSimcsekli Lingjiong Zhu 33 29 0 09 Jun 2021
Constrained and Composite Optimization via Adaptive Sampling Methods Yuchen Xie Raghu Bollapragada R. Byrd J. Nocedal 19 14 0 31 Dec 2020
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol S. Zohren Stephen J. Roberts ODL 37 49 0 16 Jun 2020
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization Thomas O'Leary-Roseberry Nick Alger Omar Ghattas ODL 37 9 0 07 Feb 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 38 20 0 25 Oct 2019
Combining Stochastic Adaptive Cubic Regularization with Negative Curvature for Nonconvex Optimization Seonho Park Seung Hyun Jung P. Pardalos ODL 29 15 0 27 Jun 2019
GPU Accelerated Sub-Sampled Newton's Method Sudhir B. Kylasa Farbod Roosta-Khorasani Michael W. Mahoney A. Grama ODL 26 8 0 26 Feb 2018
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 36 127 0 11 Sep 2017
An inexact subsampled proximal Newton-type method for large-scale machine learning Xuanqing Liu Cho-Jui Hsieh J. Lee Yuekai Sun 32 15 0 28 Aug 2017
Optimization Methods for Supervised Machine Learning: From Linear Models to Deep Learning Frank E. Curtis K. Scheinberg 39 45 0 30 Jun 2017
Generalized Self-Concordant Functions: A Recipe for Newton-Type Methods Tianxiao Sun Quoc Tran-Dinh 22 60 0 14 Mar 2017
Exact and Inexact Subsampled Newton Methods for Optimization Raghu Bollapragada R. Byrd J. Nocedal 23 176 0 27 Sep 2016
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 42 3,172 0 15 Jun 2016
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma Murat A. Erdogdu 23 13 0 28 Nov 2015