Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence

9 May 2015

Papers citing "Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence"

34 / 34 papers shown

Title
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 31 0 0 28 Jan 2025
Stochastic Online Optimization for Cyber-Physical and Robotic Systems Hao Ma M. Zeilinger Michael Muehlebach 29 0 0 08 Apr 2024
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems Younghyun Cho James Demmel Michal Derezinski Haoyun Li Hengrui Luo Michael W. Mahoney Riley Murray 27 5 0 30 Aug 2023
Memory-Query Tradeoffs for Randomized Convex Optimization X. Chen Binghui Peng 34 6 0 21 Jun 2023
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 23 5 0 01 May 2023
A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares C. Cartis J. Fowkes Zhen Shao 14 11 0 10 Nov 2022
Explicit Second-Order Min-Max Optimization Methods with Optimal Convergence Guarantee Tianyi Lin P. Mertikopoulos Michael I. Jordan 24 11 0 23 Oct 2022
Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches Michal Derezinski 42 5 0 06 Jun 2022
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming Sen Na Michael W. Mahoney 18 7 0 27 May 2022
Augmented Newton Method for Optimization: Global Linear Rate and Momentum Interpretation M. Morshed ODL 9 1 0 23 May 2022
Efficient Convex Optimization Requires Superlinear Memory A. Marsden Vatsal Sharan Aaron Sidford Gregory Valiant 24 14 0 29 Mar 2022
Operator Sketching for Deep Unrolling Networks Junqi Tang Subhadip Mukherjee Carola-Bibiane Schönlieb 16 0 0 21 Mar 2022
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients Junqi Tang 16 2 0 14 Mar 2022
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time Zhao-quan Song Licheng Zhang Ruizhe Zhang 23 63 0 14 Dec 2021
Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization Dinesh Singh Hardik Tankaria M. Yamada ODL 26 2 0 16 Oct 2021
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning Minghan Yang Dong Xu Qiwen Cui Zaiwen Wen Pengxiang Xu 11 4 0 14 Jun 2021
Sparse sketches with small inversion bias Michal Derezinski Zhenyu Liao Edgar Dobriban Michael W. Mahoney 15 21 0 21 Nov 2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 19 15 0 17 Nov 2020
Fast and Secure Distributed Nonnegative Matrix Factorization Yuqiu Qian Conghui Tan Danhao Ding Hui Li N. Mamoulis 15 13 0 07 Sep 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 19 0 0 26 Aug 2020
Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares Optimization Jonathan Lacotte Mert Pilanci 21 23 0 10 Jun 2020
FedSplit: An algorithmic framework for fast federated optimization Reese Pathak Martin J. Wainwright FedML 32 182 0 11 May 2020
How to reduce dimension with PCA and random projections? Fan Yang Sifan Liu Edgar Dobriban David P. Woodruff 17 28 0 01 May 2020
Scalable Second Order Optimization for Deep Learning Rohan Anil Vineet Gupta Tomer Koren Kevin Regan Y. Singer ODL 6 29 0 20 Feb 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 17 20 0 25 Oct 2019
OverSketch: Approximate Matrix Multiplication for the Cloud Vipul Gupta Ryan Sherman Thomas Courtade Kannan Ramchandran 9 49 0 06 Nov 2018
Bandit-Based Monte Carlo Optimization for Nearest Neighbors Vivek Bagaria Tavor Z. Baharav G. Kamath David Tse 11 12 0 21 May 2018
Generalized Self-Concordant Functions: A Recipe for Newton-Type Methods Tianxiao Sun Quoc Tran-Dinh 8 60 0 14 Mar 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data Jialei Wang J. Lee M. Mahdavi Mladen Kolar Nathan Srebro 13 50 0 10 Oct 2016
Exact and Inexact Subsampled Newton Methods for Optimization Raghu Bollapragada R. Byrd J. Nocedal 15 176 0 27 Sep 2016
Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems Raja Giryes Yonina C. Eldar A. Bronstein Guillermo Sapiro 12 85 0 30 May 2016
SUIS: An Online Graphical Signature-Based User Identification System Séamus Lankford 14 2 0 29 May 2016
Sub-Sampled Newton Methods II: Local Convergence Rates Farbod Roosta-Khorasani Michael W. Mahoney 14 83 0 18 Jan 2016
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections C. Heinze Brian McWilliams N. Meinshausen 24 37 0 08 Jun 2015