Unbiased estimates for linear regression via volume sampling

19 May 2017

Papers citing "Unbiased estimates for linear regression via volume sampling"

27 / 27 papers shown

Title
Data Selection for ERMs Steve Hanneke Shay Moran Alexander Shlimovich Amir Yehudayoff 58 0 0 20 Apr 2025
PRIMO: Private Regression in Multiple Outcomes Seth Neel 85 0 0 07 Mar 2023
$One-pass additive-error subset selection for $\ell_{p}$ subspace approximation$ One-pass additive-error subset selection for $\ell_{p}$ subspace approximation Amit Deshpande Rameshwar Pratap 67 4 0 26 Apr 2022
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD Rémi Bardenet Subhro Ghosh Meixia Lin 83 6 0 11 Dec 2021
L1 Regression with Lewis Weights Subsampling Aditya Parulekar Advait Parulekar Eric Price 57 19 0 19 May 2021
Query Complexity of Least Absolute Deviation Regression via Robust Uniform Convergence Xue Chen Michal Derezinski 63 31 0 03 Feb 2021
On proportional volume sampling for experimental design in general spaces Arnaud Poinas Rémi Bardenet 58 5 0 09 Nov 2020
Determinantal Point Processes in Randomized Numerical Linear Algebra Michal Derezinski Michael W. Mahoney 78 81 0 07 May 2020
Kernel interpolation with continuous volume sampling Ayoub Belhadji Rémi Bardenet P. Chainais 54 23 0 22 Feb 2020
Best Principal Submatrix Selection for the Maximum Entropy Sampling Problem: Scalable Algorithms and Performance Guarantees Yongchun Li Weijun Xie 33 16 0 23 Jan 2020
Exact expressions for double descent and implicit regularization via surrogate random design Michal Derezinski Feynman T. Liang Michael W. Mahoney 82 78 0 10 Dec 2019
Flexible Modeling of Diversity with Strongly Log-Concave Distributions Joshua Robinson S. Sra Stefanie Jegelka 56 12 0 12 Jun 2019
Bayesian experimental design using regularized determinantal point processes Michal Derezinski Feynman T. Liang Michael W. Mahoney 48 26 0 10 Jun 2019
Exact sampling of determinantal point processes with sublinear time preprocessing Michal Derezinski Daniele Calandriello Michal Valko 99 55 0 31 May 2019
Distributed estimation of the inverse Hessian by determinantal averaging Michal Derezinski Michael W. Mahoney 67 31 0 28 May 2019
Minimax experimental design: Bridging the gap between statistical and worst-case approaches to least squares regression Michal Derezinski K. Clarkson Michael W. Mahoney Manfred K. Warmuth 113 25 0 04 Feb 2019
Reverse iterative volume sampling for linear regression Michal Derezinski Manfred K. Warmuth 102 43 0 06 Jun 2018
Proportional Volume Sampling and Approximation Algorithms for A-Optimal Design Aleksandar Nikolov Mohit Singh U. Tantipongpipat 115 48 0 22 Feb 2018
Leveraged volume sampling for linear regression Michal Derezinski Manfred K. Warmuth Daniel J. Hsu 93 58 0 19 Feb 2018
Active Regression via Linear-Sample Sparsification Xue Chen Eric Price 132 62 0 27 Nov 2017
A unified framework for manifold landmarking Hongteng Xu Licheng Yu Mark A. Davenport H. Zha 44 4 0 25 Oct 2017
Subsampling for Ridge Regression via Regularized Volume Sampling Michal Derezinski Manfred K. Warmuth 73 20 0 14 Oct 2017
Linear regression without correspondence Daniel J. Hsu K. Shi Xiaorui Sun 90 83 0 19 May 2017
Polynomial Time Algorithms for Dual Volume Sampling Chengtao Li Stefanie Jegelka S. Sra 54 31 0 08 Mar 2017
Determinantal point processes for machine learning Alex Kulesza B. Taskar 274 1,141 0 25 Jul 2012
Near-optimal Coresets For Least-Squares Regression Christos Boutsidis P. Drineas M. Magdon-Ismail 155 80 0 16 Feb 2012
Fast approximation of matrix coherence and statistical leverage P. Drineas M. Magdon-Ismail Michael W. Mahoney David P. Woodruff 192 534 0 18 Sep 2011