Memory-Sample Tradeoffs for Linear Regression with Small Error

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Memory-Sample Tradeoffs for Linear Regression with Small Error

18 April 2019

Gregory Valiant

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Papers citing "Memory-Sample Tradeoffs for Linear Regression with Small Error"

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Title
Lower Bounds for Parallel and Randomized Convex Optimization Jelena Diakonikolas Cristóbal Guzmán 71 44 0 05 Nov 2018
Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization Eric Balkanski Yaron Singer 51 31 0 12 Aug 2018
Detecting Correlations with Little Memory and Communication Y. Dagan Ohad Shamir 31 38 0 04 Mar 2018
How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD Zeyuan Allen-Zhu ODL 73 171 0 08 Jan 2018
Extractor-Based Time-Space Lower Bounds for Learning Sumegha Garg R. Raz Avishay Tal 32 51 0 08 Aug 2017
Accelerating Stochastic Gradient Descent For Least Squares Regression Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford 71 84 0 26 Apr 2017
Tight Complexity Bounds for Optimizing Composite Objectives Blake E. Woodworth Nathan Srebro 132 185 0 25 May 2016
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut Nicolas Flammarion Francis R. Bach ODL 59 227 0 17 Feb 2016
Fast Learning Requires Good Memory: A Time-Space Lower Bound for Parity Learning R. Raz 44 94 0 16 Feb 2016
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality M. Braverman A. Garg Tengyu Ma Huy Le Nguyen David P. Woodruff FedML 81 175 0 24 Jun 2015
Competing with the Empirical Risk Minimizer in a Single Pass Roy Frostig Rong Ge Sham Kakade Aaron Sidford 69 100 0 20 Dec 2014
Optimal rates for zero-order convex optimization: the power of two function evaluations John C. Duchi Michael I. Jordan Martin J. Wainwright Andre Wibisono 82 489 0 07 Dec 2013
Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation Ohad Shamir 107 108 0 14 Nov 2013
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm Deanna Needell Nathan Srebro Rachel A. Ward 159 555 0 21 Oct 2013
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization Ohad Shamir 417 193 0 11 Sep 2012
A concentration theorem for projections S. Dasgupta Daniel J. Hsu Nakul Verma 82 38 0 27 Jun 2012