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Robustly Learning Mixtures of $k$ Arbitrary Gaussians
v1v2v3 (latest)

Robustly Learning Mixtures of kkk Arbitrary Gaussians

Symposium on the Theory of Computing (STOC), 2020
3 December 2020
Ainesh Bakshi
Ilias Diakonikolas
Hengrui Jia
D. Kane
Pravesh Kothari
Santosh Vempala
ArXiv (abs)PDFHTML

Papers citing "Robustly Learning Mixtures of $k$ Arbitrary Gaussians"

50 / 54 papers shown
Mixtures Closest to a Given Measure: A Semidefinite Programming Approach
Mixtures Closest to a Given Measure: A Semidefinite Programming Approach
Srecko Ðurasinovic
Jean B. Lasserre
Victor Magron
81
0
0
26 Sep 2025
On the Learnability of Distribution Classes with Adaptive Adversaries
On the Learnability of Distribution Classes with Adaptive Adversaries
Tosca Lechner
Alex Bie
Gautam Kamath
169
1
0
05 Sep 2025
Robust Estimation Under Heterogeneous Corruption Rates
Robust Estimation Under Heterogeneous Corruption Rates
Syomantak Chaudhuri
Jerry Li
T. Courtade
FedML
194
0
0
20 Aug 2025
Diagonally-Weighted Generalized Method of Moments Estimation for Gaussian Mixture Modeling
Diagonally-Weighted Generalized Method of Moments Estimation for Gaussian Mixture Modeling
Liu Zhang
Oscar Mickelin
Sheng Xu
A. Singer
256
0
0
28 Jul 2025
Learning High-dimensional Gaussians from Censored Data
Learning High-dimensional Gaussians from Censored DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Arnab Bhattacharyya
C. Daskalakis
Themis Gouleakis
Yuhao Wang
352
1
0
28 Apr 2025
On Learning Parallel Pancakes with Mostly Uniform Weights
On Learning Parallel Pancakes with Mostly Uniform Weights
Ilias Diakonikolas
D. Kane
Sushrut Karmalkar
Jasper C. H. Lee
Thanasis Pittas
CoGe
255
0
0
21 Apr 2025
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
Gen Li
Changxiao Cai
Yuting Wei
DiffM
386
15
0
07 Apr 2025
Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior
Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior
Yury Polyanskiy
Mark Sellke
237
1
0
26 Mar 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas
Giannis Iakovidis
D. Kane
Thanasis Pittas
408
3
0
20 Feb 2025
Entangled Mean Estimation in High-Dimensions
Entangled Mean Estimation in High-DimensionsSymposium on the Theory of Computing (STOC), 2025
Ilias Diakonikolas
D. Kane
Sihan Liu
Thanasis Pittas
357
2
0
10 Jan 2025
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Marco Fanizza
Cambyse Rouzé
Daniel Stilck França
426
13
0
05 Nov 2024
Sample-Efficient Private Learning of Mixtures of Gaussians
Sample-Efficient Private Learning of Mixtures of GaussiansNeural Information Processing Systems (NeurIPS), 2024
Hassan Ashtiani
Mahbod Majid
Shyam Narayanan
FedML
197
0
0
04 Nov 2024
Factor Adjusted Spectral Clustering for Mixture Models
Factor Adjusted Spectral Clustering for Mixture Models
Shange Tang
Soham Jana
Jianqing Fan
332
2
0
22 Aug 2024
Robust Mixture Learning when Outliers Overwhelm Small Groups
Robust Mixture Learning when Outliers Overwhelm Small Groups
Daniil Dmitriev
Rares-Darius Buhai
Stefan Tiegel
Alexander Wolters
Gleb Novikov
Amartya Sanyal
David Steurer
Fanny Yang
279
1
0
22 Jul 2024
Distribution Learnability and Robustness
Distribution Learnability and Robustness
Shai Ben-David
Alex Bie
Gautam Kamath
Tosca Lechner
371
4
0
25 Jun 2024
Perturb-and-Project: Differentially Private Similarities and Marginals
Perturb-and-Project: Differentially Private Similarities and MarginalsInternational Conference on Machine Learning (ICML), 2024
Vincent Cohen-Addad
Tommaso dÓrsi
Alessandro Epasto
Vahab Mirrokni
Peilin Zhong
472
1
0
07 Jun 2024
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph
  Clustering
A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph ClusteringInternational Conference on Machine Learning (ICML), 2024
Vincent Cohen-Addad
Tommaso dÓrsi
Aida Mousavifar
280
1
0
07 Jun 2024
Gaussian mixtures closest to a given measure via optimal transport
Gaussian mixtures closest to a given measure via optimal transport
Jean-Bernard Lasserre
OT
289
2
0
30 Apr 2024
Private graphon estimation via sum-of-squares
Private graphon estimation via sum-of-squaresSymposium on the Theory of Computing (STOC), 2024
Hongjie Chen
Jingqiu Ding
Tommaso dÓrsi
Yiding Hua
Chih-Hung Liu
David Steurer
380
2
0
18 Mar 2024
Clustering Mixtures of Bounded Covariance Distributions Under Optimal
  Separation
Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation
Ilias Diakonikolas
Daniel M. Kane
Jasper C. H. Lee
Thanasis Pittas
231
1
0
19 Dec 2023
Learning Arithmetic Formulas in the Presence of Noise: A General
  Framework and Applications to Unsupervised Learning
Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning
Pritam Chandra
Ankit Garg
N. Kayal
Kunal Mittal
Tanmay Sinha
186
6
0
13 Nov 2023
Online Robust Mean Estimation
Online Robust Mean EstimationACM-SIAM Symposium on Discrete Algorithms (SODA), 2023
Daniel M. Kane
Ilias Diakonikolas
Hanshen Xiao
Sihan Liu
OOD
305
4
0
24 Oct 2023
SQ Lower Bounds for Learning Mixtures of Linear Classifiers
SQ Lower Bounds for Learning Mixtures of Linear ClassifiersNeural Information Processing Systems (NeurIPS), 2023
Ilias Diakonikolas
D. Kane
Yuxin Sun
329
4
0
18 Oct 2023
Learning quantum Hamiltonians at any temperature in polynomial time
Learning quantum Hamiltonians at any temperature in polynomial timeSymposium on the Theory of Computing (STOC), 2023
Ainesh Bakshi
Allen Liu
Ankur Moitra
Ewin Tang
338
47
0
03 Oct 2023
Mixtures of Gaussians are Privately Learnable with a Polynomial Number
  of Samples
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of SamplesInternational Conference on Algorithmic Learning Theory (ALT), 2023
Mohammad Afzali
H. Ashtiani
Christopher Liaw
402
7
0
07 Sep 2023
Gaussian Mixture Identifiability from degree 6 Moments
Gaussian Mixture Identifiability from degree 6 MomentsAlgebraic Statistics (AS), 2023
Alexander Taveira Blomenhofer
249
4
0
07 Jul 2023
Learning Mixtures of Gaussians Using the DDPM Objective
Learning Mixtures of Gaussians Using the DDPM ObjectiveNeural Information Processing Systems (NeurIPS), 2023
Kulin Shah
Sitan Chen
Adam R. Klivans
DiffM
303
59
0
03 Jul 2023
SQ Lower Bounds for Learning Bounded Covariance GMMs
SQ Lower Bounds for Learning Bounded Covariance GMMs
Ilias Diakonikolas
D. Kane
Thanasis Pittas
Nikos Zarifis
240
0
0
22 Jun 2023
Fit Like You Sample: Sample-Efficient Generalized Score Matching from
  Fast Mixing Diffusions
Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing DiffusionsAnnual Conference Computational Learning Theory (COLT), 2023
Yilong Qin
Andrej Risteski
DiffM
384
3
0
15 Jun 2023
A Nested Matrix-Tensor Model for Noisy Multi-view Clustering
A Nested Matrix-Tensor Model for Noisy Multi-view Clustering
Abdalgader Abubaker
Mastane Achab
Henrique X. Goulart
Merouane Debbah
204
1
0
31 May 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCAInternational Conference on Machine Learning (ICML), 2023
Ilias Diakonikolas
D. Kane
Ankit Pensia
Thanasis Pittas
OOD
280
11
0
04 May 2023
A Spectral Algorithm for List-Decodable Covariance Estimation in
  Relative Frobenius Norm
A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius NormNeural Information Processing Systems (NeurIPS), 2023
Ilias Diakonikolas
D. Kane
Jasper C. H. Lee
Ankit Pensia
Thanasis Pittas
296
1
0
01 May 2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture
  Models
Polynomial Time and Private Learning of Unbounded Gaussian Mixture ModelsInternational Conference on Machine Learning (ICML), 2023
Jamil Arbas
H. Ashtiani
Christopher Liaw
371
32
0
07 Mar 2023
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
225
3
0
23 Feb 2023
The Parametric Stability of Well-separated Spherical Gaussian Mixtures
The Parametric Stability of Well-separated Spherical Gaussian Mixtures
Hanyu Zhang
M. Meilă
207
0
0
01 Feb 2023
Private estimation algorithms for stochastic block models and mixture
  models
Private estimation algorithms for stochastic block models and mixture modelsNeural Information Processing Systems (NeurIPS), 2023
Hongjie Chen
Vincent Cohen-Addad
Tommaso dÓrsi
Alessandro Epasto
Jacob Imola
David Steurer
Stefan Tiegel
FedML
397
27
0
11 Jan 2023
Higher degree sum-of-squares relaxations robust against oblivious
  outliers
Higher degree sum-of-squares relaxations robust against oblivious outliersACM-SIAM Symposium on Discrete Algorithms (SODA), 2022
Tommaso dÓrsi
Rajai Nasser
Gleb Novikov
David Steurer
236
10
0
14 Nov 2022
Efficient Algorithms for Sparse Moment Problems without Separation
Efficient Algorithms for Sparse Moment Problems without SeparationAnnual Conference Computational Learning Theory (COLT), 2022
Zhiyuan Fan
Jun Yu Li
242
9
0
26 Jul 2022
Minimax Rates for Robust Community Detection
Minimax Rates for Robust Community DetectionIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2022
Allen Liu
Ankur Moitra
307
16
0
25 Jul 2022
List-Decodable Covariance Estimation
List-Decodable Covariance EstimationSymposium on the Theory of Computing (STOC), 2022
Misha Ivkov
Pravesh Kothari
239
8
0
22 Jun 2022
Robust Sparse Mean Estimation via Sum of Squares
Robust Sparse Mean Estimation via Sum of SquaresAnnual Conference Computational Learning Theory (COLT), 2022
Ilias Diakonikolas
D. Kane
Sushrut Karmalkar
Ankit Pensia
Thanasis Pittas
497
23
0
07 Jun 2022
Streaming Algorithms for High-Dimensional Robust Statistics
Streaming Algorithms for High-Dimensional Robust StatisticsInternational Conference on Machine Learning (ICML), 2022
Ilias Diakonikolas
D. Kane
Ankit Pensia
Thanasis Pittas
327
24
0
26 Apr 2022
Tensor Moments of Gaussian Mixture Models: Theory and Applications
Tensor Moments of Gaussian Mixture Models: Theory and Applications
João M. Pereira
Joe Kileel
T. Kolda
495
17
0
14 Feb 2022
Optimal Estimation and Computational Limit of Low-rank Gaussian Mixtures
Optimal Estimation and Computational Limit of Low-rank Gaussian MixturesAnnals of Statistics (Ann. Stat.), 2022
Zhongyuan Lyu
Dong Xia
283
13
0
22 Jan 2022
Robust Voting Rules from Algorithmic Robust Statistics
Robust Voting Rules from Algorithmic Robust Statistics
Allen Liu
Ankur Moitra
333
4
0
13 Dec 2021
Beyond Parallel Pancakes: Quasi-Polynomial Time Guarantees for
  Non-Spherical Gaussian Mixtures
Beyond Parallel Pancakes: Quasi-Polynomial Time Guarantees for Non-Spherical Gaussian Mixtures
Rares-Darius Buhai
David Steurer
CoGe
270
4
0
10 Dec 2021
Lattice-Based Methods Surpass Sum-of-Squares in Clustering
Lattice-Based Methods Surpass Sum-of-Squares in Clustering
Ilias Zadik
M. Song
Alexander S. Wein
Joan Bruna
404
42
0
07 Dec 2021
Kalman Filtering with Adversarial Corruptions
Kalman Filtering with Adversarial CorruptionsSymposium on the Theory of Computing (STOC), 2021
Sitan Chen
Frederic Koehler
Ankur Moitra
Morris Yau
AAML
196
10
0
11 Nov 2021
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance
  of Gaussians Optimally
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians OptimallyInternational Conference on Algorithmic Learning Theory (ALT), 2021
Pravesh Kothari
Peter Manohar
Brian Hu Zhang
246
18
0
22 Oct 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
302
22
0
16 Jun 2021
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