On Learning Mixtures of Well-Separated Gaussians

31 October 2017

Papers citing "On Learning Mixtures of Well-Separated Gaussians"

25 / 25 papers shown

Title
$How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance$ How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance Hongkang Li Shuai Zhang Yihua Zhang Meng Wang Sijia Liu Pin-Yu Chen 93 4 0 12 Mar 2024
Gaussian Mixture Identifiability from degree 6 Moments Alexander Taveira Blomenhofer 57 2 0 07 Jul 2023
Private estimation algorithms for stochastic block models and mixture models Hongjie Chen Vincent Cohen-Addad Tommaso dÓrsi Alessandro Epasto Jacob Imola David Steurer Stefan Tiegel FedML 87 21 0 11 Jan 2023
Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes Amir Saberi Amir Najafi S. Motahari B. Khalaj 59 5 0 09 Sep 2022
List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering Ilias Diakonikolas D. Kane Sushrut Karmalkar Ankit Pensia Thanasis Pittas 70 14 0 10 Jun 2022
Continuous LWE is as Hard as LWE & Applications to Learning Gaussian Mixtures A. Gupte Neekon Vafa Vinod Vaikuntanathan 101 39 0 06 Apr 2022
Differentially-Private Clustering of Easy Instances E. Cohen Haim Kaplan Yishay Mansour Uri Stemmer Eliad Tsfadia 71 25 0 29 Dec 2021
Clustering Mixtures with Almost Optimal Separation in Polynomial Time Jingkai Li Allen Liu 59 23 0 01 Dec 2021
Uniform Consistency in Nonparametric Mixture Models Bryon Aragam Ruiyi Yang 64 6 0 31 Aug 2021
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation David Steurer Stefan Tiegel 63 10 0 05 Jan 2021
Improved Convergence Guarantees for Learning Gaussian Mixture Models by EM and Gradient EM Nimrod Segol B. Nadler 87 13 0 03 Jan 2021
Small Covers for Near-Zero Sets of Polynomials and Learning Latent Variable Models Ilias Diakonikolas D. Kane 77 33 0 14 Dec 2020
Sparse PCA: Algorithms, Adversarial Perturbations and Certificates Tommaso dÓrsi Pravesh Kothari Gleb Novikov David Steurer AAML 112 25 0 12 Nov 2020
Continuous LWE Joan Bruna O. Regev M. Song Yi Tang 43 51 0 19 May 2020
Learning sums of powers of low-degree polynomials in the non-degenerate case A. Garg N. Kayal Chandan Saha 58 24 0 15 Apr 2020
The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians Jeongyeol Kwon Constantine Caramanis 48 5 0 02 Feb 2020
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians Gautam Kamath Or Sheffet Vikrant Singhal Jonathan R. Ullman FedML 87 48 0 09 Sep 2019
Private Hypothesis Selection Mark Bun Gautam Kamath Thomas Steinke Zhiwei Steven Wu 89 91 0 30 May 2019
EM Converges for a Mixture of Many Linear Regressions Jeongyeol Kwon Constantine Caramanis 72 40 0 28 May 2019
Scalable K-Medoids via True Error Bound and Familywise Bandits A. Babu Saurabh Agarwal Sudarshan Babu Hariharan Chandrasekaran 17 0 0 27 May 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$ -means Clustering Manuel Fernández David P. Woodruff T. Yasuda 55 7 0 15 May 2019
Iterative Least Trimmed Squares for Mixed Linear Regression Yanyao Shen Sujay Sanghavi 80 25 0 10 Feb 2019
Partial recovery bounds for clustering with the relaxed $K$ means Christophe Giraud Nicolas Verzélen 265 60 0 19 Jul 2018
Better Agnostic Clustering Via Relaxed Tensor Norms Pravesh Kothari Jacob Steinhardt 133 61 0 20 Nov 2017
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians Ilias Diakonikolas D. Kane Alistair Stewart 139 147 0 20 Nov 2017