Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression

27 November 2018

Papers citing "Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression"

8 / 8 papers shown

Title
$Stochastic Primal-Dual Method for Empirical Risk Minimization with $\mathcal{O}(1)$ Per-Iteration Complexity$ Stochastic Primal-Dual Method for Empirical Risk Minimization with $\mathcal{O}(1)$ Per-Iteration Complexity Conghui Tan Tong Zhang Shiqian Ma Ji Liu ODL 41 32 0 03 Nov 2018
Leverage Score Sampling for Faster Accelerated Regression and ERM Naman Agarwal Sham Kakade Rahul Kidambi Y. Lee Praneeth Netrapalli Aaron Sidford 103 21 0 22 Nov 2017
Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness Cameron Musco Praneeth Netrapalli Aaron Sidford Shashanka Ubaru David P. Woodruff 96 36 0 13 Apr 2017
Efficient Estimation of Partially Linear Models for Spatial Data over Complex Domain Elad Hazan Chi Jin Cameron Musco Praneeth Netrapalli 50 78 0 27 May 2016
Katyusha: The First Direct Acceleration of Stochastic Gradient Methods Zeyuan Allen-Zhu ODL 96 580 0 18 Mar 2016
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization Roy Frostig Rong Ge Sham Kakade Aaron Sidford 60 150 0 24 Jun 2015
Near-Optimal Entrywise Sampling for Data Matrices D. Achlioptas Zohar Karnin Edo Liberty 61 42 0 19 Nov 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 174 1,033 0 10 Sep 2012