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A Statistical Perspective on Randomized Sketching for Ordinary
  Least-Squares
v1v2 (latest)

A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares

Journal of machine learning research (JMLR), 2014
23 June 2014
Garvesh Raskutti
Michael W. Mahoney
ArXiv (abs)PDFHTML

Papers citing "A Statistical Perspective on Randomized Sketching for Ordinary Least-Squares"

44 / 44 papers shown
SG-OIF: A Stability-Guided Online Influence Framework for Reliable Vision Data
SG-OIF: A Stability-Guided Online Influence Framework for Reliable Vision Data
Penghao Rao
Runmin Jiang
Min Xu
143
0
0
21 Nov 2025
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp
  Guarantees
Sketching for Convex and Nonconvex Regularized Least Squares with Sharp GuaranteesInternational Conference on Learning Representations (ICLR), 2023
Yingzhen Yang
Ping Li
275
0
0
03 Nov 2023
Towards a statistical theory of data selection under weak supervision
Towards a statistical theory of data selection under weak supervisionInternational Conference on Learning Representations (ICLR), 2023
Germain Kolossov
Andrea Montanari
Pulkit Tandon
372
27
0
25 Sep 2023
Ensemble linear interpolators: The role of ensembling
Ensemble linear interpolators: The role of ensembling
Mingqi Wu
Qiang Sun
281
3
0
06 Sep 2023
Approximation and Progressive Display of Multiverse Analyses
Approximation and Progressive Display of Multiverse Analyses
Yang Liu
Tim Althoff
Jeffrey Heer
138
1
0
15 May 2023
High-dimensional analysis of double descent for linear regression with
  random projections
High-dimensional analysis of double descent for linear regression with random projectionsSIAM Journal on Mathematics of Data Science (SIMODS), 2023
Francis R. Bach
294
53
0
02 Mar 2023
Sketched Ridgeless Linear Regression: The Role of Downsampling
Sketched Ridgeless Linear Regression: The Role of DownsamplingInternational Conference on Machine Learning (ICML), 2023
Xin Chen
Yicheng Zeng
Siyue Yang
Qiang Sun
261
8
0
02 Feb 2023
Towards Practical Large-scale Randomized Iterative Least Squares Solvers
  through Uncertainty Quantification
Towards Practical Large-scale Randomized Iterative Least Squares Solvers through Uncertainty Quantification
Nathaniel Pritchard
V. Patel
300
2
0
09 Aug 2022
Density Regression with Conditional Support Points
Density Regression with Conditional Support Points
Yunlu Chen
N. Zhang
149
0
0
14 Jun 2022
Optimal subsampling for functional quantile regression
Optimal subsampling for functional quantile regressionStatistical Papers (SP), 2022
Qian Yan
Hanyu Li
Chengmei Niu
209
7
0
05 May 2022
On randomized sketching algorithms and the Tracy-Widom law
On randomized sketching algorithms and the Tracy-Widom lawStatistics and computing (Stat. Comput.), 2022
Daniel Ahfock
W. Astle
S. Richardson
261
1
0
03 Jan 2022
Learning Augmentation Distributions using Transformed Risk Minimization
Learning Augmentation Distributions using Transformed Risk Minimization
Evangelos Chatzipantazis
Stefanos Pertigkiozoglou
Kostas Daniilidis
Guang Cheng
346
18
0
16 Nov 2021
On Recovering the Best Rank-r Approximation from Few Entries
On Recovering the Best Rank-r Approximation from Few Entries
Shun Xu
M. Yuan
281
0
0
11 Nov 2021
The Internet of Federated Things (IoFT): A Vision for the Future and
  In-depth Survey of Data-driven Approaches for Federated Learning
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated LearningIEEE Access (IEEE Access), 2021
Raed Al Kontar
Naichen Shi
Xubo Yue
Seokhyun Chung
E. Byon
...
Chinedum Okwudire
Garvesh Raskutti
R. Saigal
Karandeep Singh
Ye Zhisheng
FedML
354
63
0
09 Nov 2021
Functional Principal Subspace Sampling for Large Scale Functional Data
  Analysis
Functional Principal Subspace Sampling for Large Scale Functional Data AnalysisElectronic Journal of Statistics (EJS), 2021
Shiyuan He
Xiaomeng Yan
352
5
0
08 Sep 2021
Sparse sketches with small inversion bias
Sparse sketches with small inversion biasAnnual Conference Computational Learning Theory (COLT), 2020
Michal Derezinski
Zhenyu Liao
Guang Cheng
Michael W. Mahoney
515
25
0
21 Nov 2020
Recursive Importance Sketching for Rank Constrained Least Squares:
  Algorithms and High-order Convergence
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order ConvergenceOperational Research (OR), 2020
Yuetian Luo
Wen Huang
Xudong Li
Anru R. Zhang
560
17
0
17 Nov 2020
Precise expressions for random projections: Low-rank approximation and
  randomized Newton
Precise expressions for random projections: Low-rank approximation and randomized Newton
Michal Derezinski
Feynman T. Liang
Zhenyu A. Liao
Michael W. Mahoney
486
25
0
18 Jun 2020
Lower Bounds and a Near-Optimal Shrinkage Estimator for Least Squares
  using Random Projections
Lower Bounds and a Near-Optimal Shrinkage Estimator for Least Squares using Random Projections
Srivatsan Sridhar
Mert Pilanci
Ayfer Özgür
249
5
0
15 Jun 2020
How to reduce dimension with PCA and random projections?
How to reduce dimension with PCA and random projections?IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Fan Yang
Sifan Liu
Guang Cheng
David P. Woodruff
338
36
0
01 May 2020
Randomized spectral co-clustering for large-scale directed networks
Randomized spectral co-clustering for large-scale directed networksJournal of machine learning research (JMLR), 2020
Xiao Guo
Yixuan Qiu
Hai Zhang
Xiangyu Chang
403
20
0
25 Apr 2020
Asymptotic Analysis of Sampling Estimators for Randomized Numerical
  Linear Algebra Algorithms
Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra AlgorithmsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Ping Ma
Xinlian Zhang
Xin Xing
Jingyi Ma
Michael W. Mahoney
212
71
0
24 Feb 2020
Optimal subsampling for quantile regression in big data
Optimal subsampling for quantile regression in big dataBiometrika (Biometrika), 2020
Haiying Wang
Yanyuan Ma
349
155
0
28 Jan 2020
Randomized Spectral Clustering in Large-Scale Stochastic Block Models
Randomized Spectral Clustering in Large-Scale Stochastic Block ModelsJournal of Computational And Graphical Statistics (JCGS), 2020
Hai Zhang
Xiao Guo
Xiangyu Chang
503
31
0
20 Jan 2020
Exact minimax risk for linear least squares, and the lower tail of
  sample covariance matrices
Exact minimax risk for linear least squares, and the lower tail of sample covariance matricesAnnals of Statistics (Ann. Stat.), 2019
Jaouad Mourtada
284
57
0
23 Dec 2019
Exact expressions for double descent and implicit regularization via
  surrogate random design
Exact expressions for double descent and implicit regularization via surrogate random designNeural Information Processing Systems (NeurIPS), 2019
Michal Derezinski
Feynman T. Liang
Michael W. Mahoney
412
79
0
10 Dec 2019
Histogram Transform Ensembles for Large-scale Regression
Histogram Transform Ensembles for Large-scale RegressionJournal of machine learning research (JMLR), 2019
H. Hang
Zhouchen Lin
Xiaoyu Liu
Hongwei Wen
215
2
0
08 Dec 2019
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of
  Big Time Series Data
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series DataJournal of machine learning research (JMLR), 2019
A. Eshragh
Fred Roosta
A. Nazari
Michael W. Mahoney
AI4TS
280
17
0
27 Nov 2019
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance
  Sketching
ISLET: Fast and Optimal Low-rank Tensor Regression via Importance SketchingSIAM Journal on Mathematics of Data Science (SIMODS), 2019
Anru R. Zhang
Yuetian Luo
Garvesh Raskutti
M. Yuan
603
51
0
09 Nov 2019
Ridge Regression: Structure, Cross-Validation, and Sketching
Ridge Regression: Structure, Cross-Validation, and SketchingInternational Conference on Learning Representations (ICLR), 2019
Sifan Liu
Guang Cheng
CML
496
52
0
06 Oct 2019
Optimal Sampling for Generalized Linear Models under Measurement
  Constraints
Optimal Sampling for Generalized Linear Models under Measurement ConstraintsJournal of Computational And Graphical Statistics (JCGS), 2019
Tao Zhang
Y. Ning
D. Ruppert
322
40
0
17 Jul 2019
An Econometric Perspective on Algorithmic Subsampling
An Econometric Perspective on Algorithmic SubsamplingAnnual Review of Economics (ARE), 2019
Serena Ng
S. Lee
439
14
0
03 Jul 2019
Two-stage Best-scored Random Forest for Large-scale Regression
Two-stage Best-scored Random Forest for Large-scale Regression
H. Hang
Yingyi Chen
Johan A. K. Suykens
122
0
0
09 May 2019
A determinantal point process for column subset selection
A determinantal point process for column subset selection
Ayoub Belhadji
Rémi Bardenet
P. Chainais
138
29
0
23 Dec 2018
Asymptotics for Sketching in Least Squares Regression
Asymptotics for Sketching in Least Squares Regression
Guang Cheng
Sifan Liu
234
14
0
14 Oct 2018
A Projector-Based Approach to Quantifying Total and Excess Uncertainties
  for Sketched Linear Regression
A Projector-Based Approach to Quantifying Total and Excess Uncertainties for Sketched Linear Regression
Jocelyn T. Chi
Ilse C. F. Ipsen
221
5
0
17 Aug 2018
Subspace Embedding and Linear Regression with Orlicz Norm
Subspace Embedding and Linear Regression with Orlicz Norm
Alexandr Andoni
Chengyu Lin
Ying Sheng
Peilin Zhong
Ruiqi Zhong
190
39
0
17 Jun 2018
Optimal Sub-sampling with Influence Functions
Optimal Sub-sampling with Influence Functions
Daniel Ting
E. Brochu
TDI
183
32
0
06 Sep 2017
Statistical properties of sketching algorithms
Statistical properties of sketching algorithms
Daniel Ahfock
W. Astle
S. Richardson
235
42
0
12 Jun 2017
Sketched Ridge Regression: Optimization Perspective, Statistical
  Perspective, and Model Averaging
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model AveragingInternational Conference on Machine Learning (ICML), 2017
Shusen Wang
Alex Gittens
Michael W. Mahoney
365
86
0
16 Feb 2017
Sketching Meets Random Projection in the Dual: A Provable Recovery
  Algorithm for Big and High-dimensional Data
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2016
Jialei Wang
Jason D. Lee
M. Mahdavi
Mladen Kolar
Nathan Srebro
334
51
0
10 Oct 2016
Online Censoring for Large-Scale Regressions with Application to
  Streaming Big Data
Online Censoring for Large-Scale Regressions with Application to Streaming Big DataIEEE Transactions on Signal Processing (IEEE TSP), 2015
Dimitris Berberidis
V. Kekatos
G. Giannakis
268
69
0
27 Jul 2015
Statistical and Algorithmic Perspectives on Randomized Sketching for
  Ordinary Least-Squares -- ICML
Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares -- ICMLInternational Conference on Machine Learning (ICML), 2015
Garvesh Raskutti
Michael W. Mahoney
205
16
0
25 May 2015
The Statistics of Streaming Sparse Regression
The Statistics of Streaming Sparse Regression
Jacob Steinhardt
Stefan Wager
Abigail Z. Jacobs
560
11
0
13 Dec 2014
1
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