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1802.06749
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Leveraged volume sampling for linear regression
19 February 2018
Michal Derezinski
Manfred K. Warmuth
Daniel J. Hsu
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Papers citing
"Leveraged volume sampling for linear regression"
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Improved Active Learning via Dependent Leverage Score Sampling
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Xiaoou Cheng
Chris Musco
Jonathan Weare
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Juan M. Cardenas
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Improved Financial Forecasting via Quantum Machine Learning
Quantum Machine Intelligence (QMI), 2023
Sohum Thakkar
Skander Kazdaghli
Natansh Mathur
Iordanis Kerenidis
A. J. Ferreira-Martins
Samurai Brito QC Ware Corp
AIFin
253
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31 May 2023
Optimal Sublinear Sampling of Spanning Trees and Determinantal Point Processes via Average-Case Entropic Independence
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2022
Nima Anari
Yang P. Liu
T. Vuong
440
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06 Apr 2022
Semi-supervised Active Regression
Fnu Devvrit
Nived Rajaraman
Pranjal Awasthi
262
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12 Jun 2021
Query Complexity of Least Absolute Deviation Regression via Robust Uniform Convergence
Annual Conference Computational Learning Theory (COLT), 2021
Xue Chen
Michal Derezinski
334
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0
03 Feb 2021
Sparse sketches with small inversion bias
Annual Conference Computational Learning Theory (COLT), 2020
Michal Derezinski
Zhenyu Liao
Guang Cheng
Michael W. Mahoney
515
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21 Nov 2020
On proportional volume sampling for experimental design in general spaces
Arnaud Poinas
Rémi Bardenet
368
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09 Nov 2020
Sampling from a
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Daniele Calandriello
Michal Derezinski
Michal Valko
277
29
0
30 Jun 2020
Active Online Learning with Hidden Shifting Domains
Yining Chen
Haipeng Luo
Tengyu Ma
Chicheng Zhang
281
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25 Jun 2020
Fourier Sparse Leverage Scores and Approximate Kernel Learning
Neural Information Processing Systems (NeurIPS), 2020
T. Erdélyi
Cameron Musco
Christopher Musco
384
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0
12 Jun 2020
Determinantal Point Processes in Randomized Numerical Linear Algebra
Michal Derezinski
Michael W. Mahoney
282
93
0
07 May 2020
Kernel interpolation with continuous volume sampling
International Conference on Machine Learning (ICML), 2020
Ayoub Belhadji
Rémi Bardenet
P. Chainais
184
26
0
22 Feb 2020
Exact expressions for double descent and implicit regularization via surrogate random design
Neural Information Processing Systems (NeurIPS), 2019
Michal Derezinski
Feynman T. Liang
Michael W. Mahoney
414
79
0
10 Dec 2019
Random Quadratic Forms with Dependence: Applications to Restricted Isometry and Beyond
Neural Information Processing Systems (NeurIPS), 2019
A. Banerjee
Qilong Gu
V. Sivakumar
Zhiwei Steven Wu
274
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0
11 Oct 2019
Bayesian Batch Active Learning as Sparse Subset Approximation
Neural Information Processing Systems (NeurIPS), 2019
Tian Xie
Jonathan Gordon
Eric T. Nalisnick
José Miguel Hernández-Lobato
UQCV
479
148
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06 Aug 2019
Unbiased estimators for random design regression
Journal of machine learning research (JMLR), 2019
Michal Derezinski
Manfred K. Warmuth
Daniel J. Hsu
288
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0
08 Jul 2019
Bayesian experimental design using regularized determinantal point processes
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Michal Derezinski
Feynman T. Liang
Michael W. Mahoney
219
27
0
10 Jun 2019
Exact sampling of determinantal point processes with sublinear time preprocessing
Neural Information Processing Systems (NeurIPS), 2019
Michal Derezinski
Daniele Calandriello
Michal Valko
299
58
0
31 May 2019
Distributed estimation of the inverse Hessian by determinantal averaging
Neural Information Processing Systems (NeurIPS), 2019
Michal Derezinski
Michael W. Mahoney
230
32
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
325
28
0
04 Feb 2019
A determinantal point process for column subset selection
Ayoub Belhadji
Rémi Bardenet
P. Chainais
140
29
0
23 Dec 2018
Fast determinantal point processes via distortion-free intermediate sampling
Annual Conference Computational Learning Theory (COLT), 2018
Michal Derezinski
367
40
0
08 Nov 2018
Correcting the bias in least squares regression with volume-rescaled sampling
Michal Derezinski
Manfred K. Warmuth
Daniel J. Hsu
167
15
0
04 Oct 2018
Determinantal Point Processes for Coresets
Nicolas M Tremblay
Simon Barthelmé
P. Amblard
492
35
0
23 Mar 2018
Unbiased estimates for linear regression via volume sampling
Michal Derezinski
Manfred K. Warmuth
454
55
0
19 May 2017
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