Robust \(k\)-means clustering for distributions with two moments
type: Item
instance of: scholarly article
title: Robust \(k\)-means clustering for distributions with two moments
zbMATH Open document ID: 1487.62070
DOI: 10.1214/20-AOS2033
author: Yegor Klochkov
author: Alexey Kroshnin
author: Nikita Zhivotovskiy
published in: The Annals of Statistics
publication date: 2021-12-03T00:00:00Z
full work available at URL: https://arxiv.org/abs/2002.02339
full work available at URL: 20-AOS2033.full
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62F35
Mathematics Subject Classification ID: 62F12
zbMATH DE Number: 7438240
zbMATH Keywords: clustering
zbMATH Keywords: excess distortion bounds
zbMATH Keywords: \(k\)-means
zbMATH Keywords: robust estimation
MaRDI profile type: Publication
arXiv ID: 2002.02339
cites work: The space complexity of approximating the frequency moments
cites work: Improved Minimax Bounds on the Test and Training Distortion of Empirically Designed Vector Quantizers
cites work: The minimax distortion redundancy in empirical quantizer design
cites work: On the Performance of Clustering in Hilbert Spaces
cites work: Theory of Classification: a Survey of Some Recent Advances
cites work: Concentration inequalities. A nonasymptotic theory of independence
cites work: Robust Bregman clustering
cites work: Empirical risk minimization for heavy-tailed losses
cites work: On Hölder fields clustering
cites work: Testing the manifold hypothesis
cites work: Quantization and clustering with Bregman divergences
cites work: Foundations of quantization for probability distributions
cites work: Extensions of Lipschitz mappings into a Hilbert space
cites work: Robust machine learning by median-of-means: theory and practice
cites work: Robust classification via MOM minimization
cites work: Fast rates for empirical vector quantization
cites work: Nonasymptotic bounds for vector quantization in Hilbert spaces
cites work: Near-optimal mean estimators with respect to general norms
cites work: Regularization, sparse recovery, and median-of-means tournaments
cites work: Sub-Gaussian estimators of the mean of a random vector
cites work: A Vector-Contraction Inequality for Rademacher Complexities
cites work: $K$-Dimensional Coding Schemes in Hilbert Spaces
cites work: Robust covariance estimation under \(L_4\)-\(L_2\) norm equivalence
cites work: Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed entries
cites work: Q3967358
cites work: Strong consistency of k-means clustering
cites work: Upper and Lower Bounds for Stochastic Processes
cites work: Q4770512
cites work: High-Dimensional Probability
OpenAlex ID: W3204688258
Recommended article: Robust moment estimation and improved clustering via sum of squares
Recommended article: Q3572405
Recommended article: Robust and sparse \(k\)-means clustering for high-dimensional data
Recommended article: Robust Hierarchical k-Center Clustering
Recommended article: Robust estimation of the mean vector for high-dimensional data set using robust clustering
Recommended article: Q3169463
Recommended article: A review of robust clustering methods
Recommended article: Some refinements of rough \(k\)-means clustering
Recommended article: Q3562847
description: scientific article