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List-Decodable Subspace Recovery: Dimension Independent Error in
  Polynomial Time
v1v2v3 (latest)

List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time

12 February 2020
Ainesh Bakshi
Pravesh Kothari
ArXiv (abs)PDFHTML

Papers citing "List-Decodable Subspace Recovery: Dimension Independent Error in Polynomial Time"

15 / 15 papers shown
Beyond Moments: Robustly Learning Affine Transformations with
  Asymptotically Optimal Error
Beyond Moments: Robustly Learning Affine Transformations with Asymptotically Optimal ErrorIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2023
He Jia
Pravesh Kothari
Santosh Vempala
230
3
0
23 Feb 2023
A New Approach to Learning Linear Dynamical Systems
A New Approach to Learning Linear Dynamical SystemsSymposium on the Theory of Computing (STOC), 2023
Ainesh Bakshi
Allen Liu
Ankur Moitra
Morris Yau
279
27
0
23 Jan 2023
List-Decodable Covariance Estimation
List-Decodable Covariance EstimationSymposium on the Theory of Computing (STOC), 2022
Misha Ivkov
Pravesh Kothari
249
8
0
22 Jun 2022
Private Robust Estimation by Stabilizing Convex Relaxations
Private Robust Estimation by Stabilizing Convex Relaxations
Pravesh Kothari
Pasin Manurangsi
A. Velingker
280
51
0
07 Dec 2021
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean
  Estimation
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
Haibin Zhang
Kevin Tian
FedML
315
22
0
16 Jun 2021
Semi-verified PAC Learning from the Crowd
Semi-verified PAC Learning from the CrowdInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Shiwei Zeng
Jie Shen
342
4
0
13 Jun 2021
Robust and Differentially Private Mean Estimation
Robust and Differentially Private Mean EstimationNeural Information Processing Systems (NeurIPS), 2021
Xiyang Liu
Weihao Kong
Sham Kakade
Sewoong Oh
OODFedML
348
85
0
18 Feb 2021
Robustly Learning Mixtures of $k$ Arbitrary Gaussians
Robustly Learning Mixtures of kkk Arbitrary GaussiansSymposium on the Theory of Computing (STOC), 2020
Ainesh Bakshi
Ilias Diakonikolas
Hengrui Jia
D. Kane
Pravesh Kothari
Santosh Vempala
584
73
0
03 Dec 2020
List-Decodable Mean Estimation in Nearly-PCA Time
List-Decodable Mean Estimation in Nearly-PCA TimeNeural Information Processing Systems (NeurIPS), 2020
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
Haibin Zhang
Kevin Tian
252
17
0
19 Nov 2020
Robust Linear Regression: Optimal Rates in Polynomial Time
Robust Linear Regression: Optimal Rates in Polynomial Time
Ainesh Bakshi
Adarsh Prasad
507
63
0
29 Jun 2020
List-Decodable Mean Estimation via Iterative Multi-Filtering
List-Decodable Mean Estimation via Iterative Multi-Filtering
Ilias Diakonikolas
D. Kane
Daniel Kongsgaard
248
23
0
18 Jun 2020
Robust Meta-learning for Mixed Linear Regression with Small Batches
Robust Meta-learning for Mixed Linear Regression with Small Batches
Weihao Kong
Raghav Somani
Sham Kakade
Sewoong Oh
OOD
275
38
0
17 Jun 2020
Robustly Learning any Clusterable Mixture of Gaussians
Robustly Learning any Clusterable Mixture of Gaussians
Ilias Diakonikolas
Samuel B. Hopkins
D. Kane
Sushrut Karmalkar
334
48
0
13 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures
Outlier-Robust Clustering of Non-Spherical Mixtures
Ainesh Bakshi
Pravesh Kothari
481
35
0
06 May 2020
List Decodable Subspace Recovery
List Decodable Subspace RecoveryAnnual Conference Computational Learning Theory (COLT), 2020
P. Raghavendra
Morris Yau
311
24
0
07 Feb 2020
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