Robust Learning of Mixtures of Gaussians

Ilias Diakonikolas, Daniel M. Kane Recent Advances in Algorithmic High-Dimensional Robust Statistics , https://arxiv.org/abs/1911.05911

Original

1911

Earlier work this paper cites.

F. R. Hampel, E. M. Ronchetti, P. J. Rousseeuw, and W. A. Stahel, Robust statistics the approach based on influence functions , Wiley New York, 1986

1986

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S. Dasgupta, Learning mixtures of Gaussians , Proceedings of the 40th Annual Symposiumon Foundations of Computer Science, 1999, pp. 634-–644

1999

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S. Arora, R. Kannan, Learning mixtures of arbitrary Gaussians , Proceedings of the33rd Symposium on Theory of Computing, 2001, pp. 247-–257

2001

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S. Vempala, G. Wang, A spectral algorithm for learning mixtures of distributions , Proceedings of the 43rd IEEE Symposium on Foundations of Computer Science (FOCS), 2002, pp. 113–-122

2002

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D. Achlioptas, F. McSherry, On spectral learning of mixtures of distributions , Proceedings of the 18th Annual Conference on Learning Theory (COLT), 2005, pp. 458-–469

2005

Earlier work this paper cites.

Ainesh Bakshi, Pravesh Kothari, Outlier-Robust Clustering of Non-Spherical Mixtures , https://arxiv.org/abs/2005.02970

Original

2005

Earlier work this paper cites.

Ilias Diakonikolas, Samuel B. Hopkins, Daniel Kane, Sushrut Karmalkar, Robustly Learning any Clusterable Mixture of Gaussians , https://arxiv.org/abs/2005.06417

Original

2005

Earlier work this paper cites.

J. Feldman, R. O’Donnell, R. Servedio, PAC learning mixtures of Gaussians with noseparation assumption , Proceedings of the 19th Annual Conference on Learning Theory (COLT), 2006, pp. 20-–34

2006

Cited alongside, same era.

S. C. Brubaker, S. Vempala, Isotropic PCA and Affine-Invariant Clustering , Proceedings of the 49th IEEE Symposium on Foundations of Computer Science (FOCS), 2008, pp. 551-–560

2008

Cited alongside, same era.

R. Kannan, H. Salmasian, S. Vempala, The spectral method for general mixture models ,SIAM Journal of Computation 38(2008), no. 3, pp. 1141-–1156

2008

Cited alongside, same era.

P. J. Huber and E. M. Ronchetti, Robust statistics , Wiley New York, 2009

2009

Cited alongside, same era.

M. Belkin, K. Sinha, Polynomial learning of distribution families , Foundations of Computer Science (FOCS), 2010, pp. 103-–112

2010

C. Daskalakis, G. Kamath, Faster and sample near-optimal algorithms for proper learningmixtures of Gaussians , Proceedings of the 27th Annual Conference on Learning Theory (COLT), 2014, pp. 1183-–1213

2014

Later among the works it cites.

A. T. Suresh, A. Orlitsky, J. Acharya, A. Jafarpour, Near-optimal-sample estimatorsfor spherical Gaussian mixtures , Proceedings of the 29th Annual Conference on Neural Information Processing Systems (NeurIPS), 2014, pp. 1395-–1403

2014

Later among the works it cites.

Moritz Hardt and Eric Price, Tight Bounds for Learning a Mixture of Two Gaussians , Symposium on the Theory Of Computation (STOC), 2015

2015

Later among the works it cites.

K. A. Lai, A. B. Rao, and S. Vempala Agnostic estimationof mean and covariance , In Proceedings of the 57th IEEE Symposium on Foundations of Computer Science (FOCS), 2016 pages 665-–674

2016

Later among the works it cites.