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Algorithms and Hardness for Robust Subspace Recovery
v1v2v3 (latest)

Algorithms and Hardness for Robust Subspace Recovery

5 November 2012
Moritz Hardt
Ankur Moitra
    OOD
ArXiv (abs)PDFHTML

Papers citing "Algorithms and Hardness for Robust Subspace Recovery"

50 / 59 papers shown
Title
The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
Adam R. Klivans
Konstantinos Stavropoulos
Kevin Tian
Arsen Vasilyan
39
0
0
26 May 2025
Inapproximability of Finding Sparse Vectors in Codes, Subspaces, and Lattices
Inapproximability of Finding Sparse Vectors in Codes, Subspaces, and Lattices
V. Bhattiprolu
Venkatesan Guruswami
Euiwoong Lee
Xuandi Ren
26
1
0
03 Oct 2024
Disciplined Geodesically Convex Programming
Disciplined Geodesically Convex Programming
Andrew Cheng
Vaibhav Dixit
Melanie Weber
140
1
0
07 Jul 2024
A Subspace-Constrained Tyler's Estimator and its Applications to
  Structure from Motion
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion
Feng Yu
Teng Zhang
Gilad Lerman
61
3
0
17 Apr 2024
Theoretical Guarantees for the Subspace-Constrained Tyler's Estimator
Theoretical Guarantees for the Subspace-Constrained Tyler's Estimator
Gilad Lerman
Feng Yu
Teng Zhang
41
1
0
27 Mar 2024
A Combinatorial Approach to Robust PCA
A Combinatorial Approach to Robust PCA
Weihao Kong
Mingda Qiao
Rajat Sen
46
0
0
28 Nov 2023
Distribution-Independent Regression for Generalized Linear Models with
  Oblivious Corruptions
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions
Ilias Diakonikolas
Sushrut Karmalkar
Jongho Park
Christos Tzamos
57
1
0
20 Sep 2023
Self-Directed Linear Classification
Self-Directed Linear Classification
Ilias Diakonikolas
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
60
4
0
06 Aug 2023
A Strongly Polynomial Algorithm for Approximate Forster Transforms and
  its Application to Halfspace Learning
A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning
Ilias Diakonikolas
Christos Tzamos
D. Kane
60
13
0
06 Dec 2022
Local Linear Convergence of Gradient Methods for Subspace Optimization
  via Strict Complementarity
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity
Dan Garber
Ron Fisher
68
1
0
08 Feb 2022
Private and polynomial time algorithms for learning Gaussians and beyond
Private and polynomial time algorithms for learning Gaussians and beyond
H. Ashtiani
Christopher Liaw
131
48
0
22 Nov 2021
ReLU Regression with Massart Noise
ReLU Regression with Massart Noise
Ilias Diakonikolas
Jongho Park
Christos Tzamos
109
12
0
10 Sep 2021
Excess Capacity and Backdoor Poisoning
Excess Capacity and Backdoor Poisoning
N. Manoj
Avrim Blum
SILMAAML
83
24
0
02 Sep 2021
Forster Decomposition and Learning Halfspaces with Noise
Forster Decomposition and Learning Halfspaces with Noise
Ilias Diakonikolas
D. Kane
Christos Tzamos
136
19
0
12 Jul 2021
Closed-Form, Provable, and Robust PCA via Leverage Statistics and
  Innovation Search
Closed-Form, Provable, and Robust PCA via Leverage Statistics and Innovation Search
M. Rahmani
Ping Li
46
5
0
23 Jun 2021
On Subspace Approximation and Subset Selection in Fewer Passes by MCMC
  Sampling
On Subspace Approximation and Subset Selection in Fewer Passes by MCMC Sampling
Amit Deshpande
Rameshwar Pratap
13
0
0
20 Mar 2021
Settling the Robust Learnability of Mixtures of Gaussians
Settling the Robust Learnability of Mixtures of Gaussians
Allen Liu
Ankur Moitra
79
42
0
06 Nov 2020
Maximizing Welfare with Incentive-Aware Evaluation Mechanisms
Maximizing Welfare with Incentive-Aware Evaluation Mechanisms
Nika Haghtalab
Nicole Immorlica
Brendan Lucier
Jack Z. Wang
73
72
0
03 Nov 2020
Computationally and Statistically Efficient Truncated Regression
Computationally and Statistically Efficient Truncated Regression
C. Daskalakis
Themis Gouleakis
Christos Tzamos
Manolis Zampetakis
58
32
0
22 Oct 2020
Online and Distribution-Free Robustness: Regression and Contextual
  Bandits with Huber Contamination
Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination
Sitan Chen
Frederic Koehler
Ankur Moitra
Morris Yau
78
35
0
08 Oct 2020
Subspace approximation with outliers
Subspace approximation with outliers
Amit Deshpande
Rameshwar Pratap
47
3
0
30 Jun 2020
List-Decodable Subspace Recovery: Dimension Independent Error in
  Polynomial Time
List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time
Ainesh Bakshi
Pravesh Kothari
85
23
0
12 Feb 2020
On Robust Mean Estimation under Coordinate-level Corruption
On Robust Mean Estimation under Coordinate-level Corruption
Zifan Liu
Jongho Park
Theodoros Rekatsinas
Christos Tzamos
76
8
0
10 Feb 2020
List Decodable Subspace Recovery
List Decodable Subspace Recovery
P. Raghavendra
Morris Yau
103
26
0
07 Feb 2020
Rigorous Guarantees for Tyler's M-estimator via quantum expansion
Rigorous Guarantees for Tyler's M-estimator via quantum expansion
Cole Franks
Ankur Moitra
67
26
0
31 Jan 2020
Outlier Detection and Data Clustering via Innovation Search
Outlier Detection and Data Clustering via Innovation Search
M. Rahmani
P. Li
73
3
0
30 Dec 2019
Recent Advances in Algorithmic High-Dimensional Robust Statistics
Recent Advances in Algorithmic High-Dimensional Robust Statistics
Ilias Diakonikolas
D. Kane
OOD
93
184
0
14 Nov 2019
Robust Risk Minimization for Statistical Learning
Robust Risk Minimization for Statistical Learning
Muhammad Osama
Dave Zachariah
Petre Stoica
OOD
25
7
0
03 Oct 2019
Robust Subspace Recovery with Adversarial Outliers
Robust Subspace Recovery with Adversarial Outliers
Tyler Maunu
Gilad Lerman
60
19
0
05 Apr 2019
How Hard Is Robust Mean Estimation?
How Hard Is Robust Mean Estimation?
Samuel B. Hopkins
Jerry Li
38
37
0
19 Mar 2019
Smoothed Analysis in Unsupervised Learning via Decoupling
Smoothed Analysis in Unsupervised Learning via Decoupling
Aditya Bhaskara
Aidao Chen
Aidan Perreault
Aravindan Vijayaraghavan
54
19
0
29 Nov 2018
Testing Matrix Rank, Optimally
Testing Matrix Rank, Optimally
Maria-Florina Balcan
Yi Li
David P. Woodruff
Hongyang R. Zhang
90
24
0
18 Oct 2018
Efficient Statistics, in High Dimensions, from Truncated Samples
Efficient Statistics, in High Dimensions, from Truncated Samples
C. Daskalakis
Themis Gouleakis
Christos Tzamos
Manolis Zampetakis
102
50
0
11 Sep 2018
Geodesic Convex Optimization: Differentiation on Manifolds, Geodesics,
  and Convexity
Geodesic Convex Optimization: Differentiation on Manifolds, Geodesics, and Convexity
Nisheeth K. Vishnoi
57
38
0
17 Jun 2018
An Overview of Robust Subspace Recovery
An Overview of Robust Subspace Recovery
Gilad Lerman
Tyler Maunu
84
131
0
02 Mar 2018
RANSAC Algorithms for Subspace Recovery and Subspace Clustering
RANSAC Algorithms for Subspace Recovery and Subspace Clustering
E. Arias-Castro
Jue Wang
70
10
0
30 Nov 2017
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery
Tyler Maunu
Teng Zhang
Gilad Lerman
75
63
0
13 Jun 2017
Recovery Guarantees for One-hidden-layer Neural Networks
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong
Zhao Song
Prateek Jain
Peter L. Bartlett
Inderjit S. Dhillon
MLT
186
337
0
10 Jun 2017
Matrix Completion and Related Problems via Strong Duality
Matrix Completion and Related Problems via Strong Duality
Maria-Florina Balcan
Yingyu Liang
David P. Woodruff
Hongyang R. Zhang
70
8
0
27 Apr 2017
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jerry Li
Ankur Moitra
Alistair Stewart
102
135
0
12 Apr 2017
Robust Sparse Estimation Tasks in High Dimensions
Robust Sparse Estimation Tasks in High Dimensions
Jerry Li
118
27
0
20 Feb 2017
Low Rank Matrix Recovery with Simultaneous Presence of Outliers and
  Sparse Corruption
Low Rank Matrix Recovery with Simultaneous Presence of Outliers and Sparse Corruption
M. Rahmani
George Atia
29
6
0
07 Feb 2017
Robust Low-Complexity Randomized Methods for Locating Outliers in Large
  Matrices
Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices
Xingguo Li
Jarvis Haupt
32
2
0
07 Dec 2016
Learning from Untrusted Data
Learning from Untrusted Data
Moses Charikar
Jacob Steinhardt
Gregory Valiant
FedMLOOD
134
300
0
07 Nov 2016
Generalized Topic Modeling
Generalized Topic Modeling
Avrim Blum
Nika Haghtalab
OOD
13
3
0
04 Nov 2016
Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis
Coherence Pursuit: Fast, Simple, and Robust Principal Component Analysis
M. Rahmani
George Atia
101
135
0
15 Sep 2016
Conditional Sparse Linear Regression
Conditional Sparse Linear Regression
Brendan Juba
44
12
0
18 Aug 2016
Robust Learning of Fixed-Structure Bayesian Networks
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng
Ilias Diakonikolas
D. Kane
Alistair Stewart
OOD
121
47
0
23 Jun 2016
Robust Estimators in High Dimensions without the Computational
  Intractability
Robust Estimators in High Dimensions without the Computational Intractability
Ilias Diakonikolas
Gautam Kamath
D. Kane
Jingkai Li
Ankur Moitra
Alistair Stewart
102
513
0
21 Apr 2016
Intersecting Faces: Non-negative Matrix Factorization With New
  Guarantees
Intersecting Faces: Non-negative Matrix Factorization With New Guarantees
Rong Ge
James Zou
CVBM
82
24
0
08 Jul 2015
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