Sub-Sampled Newton Methods I: Globally Convergent Algorithms

18 January 2016

Papers citing "Sub-Sampled Newton Methods I: Globally Convergent Algorithms"

19 / 19 papers shown

Title
ISAAC Newton: Input-based Approximate Curvature for Newton's Method Felix Petersen Tobias Sutter Christian Borgelt Dongsung Huh Hilde Kuehne Yuekai Sun Oliver Deussen ODL 47 5 0 01 May 2023
An Efficient Nonlinear Acceleration method that Exploits Symmetry of the Hessian Huan He Shifan Zhao Z. Tang Joyce C. Ho Y. Saad Yuanzhe Xi 37 3 0 22 Oct 2022
On randomized sketching algorithms and the Tracy-Widom law Daniel Ahfock W. Astle S. Richardson 28 1 0 03 Jan 2022
Constrained and Composite Optimization via Adaptive Sampling Methods Yuchen Xie Raghu Bollapragada R. Byrd J. Nocedal 27 14 0 31 Dec 2020
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning Z. Yao A. Gholami Sheng Shen Mustafa Mustafa Kurt Keutzer Michael W. Mahoney ODL 39 275 0 01 Jun 2020
Low Rank Saddle Free Newton: A Scalable Method for Stochastic Nonconvex Optimization Thomas O'Leary-Roseberry Nick Alger Omar Ghattas ODL 42 9 0 07 Feb 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 38 21 0 25 Oct 2019
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham T. Dzung Lam M. Nguyen 27 49 0 08 Jul 2019
OverSketched Newton: Fast Convex Optimization for Serverless Systems Vipul Gupta S. Kadhe T. Courtade Michael W. Mahoney Kannan Ramchandran 19 33 0 21 Mar 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 Jason D. Lee Yuekai Sun 35 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
Statistical properties of sketching algorithms Daniel Ahfock W. Astle S. Richardson 29 37 0 12 Jun 2017
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method Mark Eisen Aryan Mokhtari Alejandro Ribeiro 35 16 0 22 May 2017
Generalized Self-Concordant Functions: A Recipe for Newton-Type Methods Tianxiao Sun Quoc Tran-Dinh 24 60 0 14 Mar 2017
Exact and Inexact Subsampled Newton Methods for Optimization Raghu Bollapragada R. Byrd J. Nocedal 23 178 0 27 Sep 2016
Sub-Sampled Newton Methods II: Local Convergence Rates Farbod Roosta-Khorasani Michael W. Mahoney 33 84 0 18 Jan 2016
Newton-Stein Method: An optimization method for GLMs via Stein's Lemma Murat A. Erdogdu 29 13 0 28 Nov 2015