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Coreset (or core-set) is a small weighted \emph{subset} $Q$ of an input set $P$ with respect to a given \emph{monotonic} function $f:\mathbb{R}\to\mathbb{R}$ that \emph{provably} approximates its fitting loss $\sum_{p\in P}f(p\cdot x)$ to \emph{any} given $x\in\mathbb{R}^d$.
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M. Langberg and L. J. Schulman · 2010
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Scalable training of mixture models via coresets
Dan Feldman, Matthew Faulkner, and Andreas Krause · 2011
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A unified framework for approximating and clustering data
Dan Feldman and Michael Langberg · 2011
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Data reduction for weighted and outlier-resistant clustering
Dan Feldman and Leonard J Schulman · 2012
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Hiroshi Kajino, Yuta Tsuboi, and Hisashi Kashima · 2012
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Coresets for scalable bayesian logistic regression
Jonathan Huggins, Trevor Campbell, and Tamara Broderick · 2016
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Regularization for deep learning: A taxonomy
Jan Kukačka, Vladimir Golkov, and Daniel Cremers · 2017
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Training gaussian mixture models at scale via coresets
Mario Lucic, Matthew Faulkner, Andreas Krause, and Dan Feldman · 2017
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Coresets for kernel regression
Yan Zheng and Jeff M Phillips · 2017
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On coresets for logistic regression
Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, and David Woodruff · 2018
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Kasturi Varadarajan and Xin Xiao · 2012
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Near-optimal coresets for least-squares regression
Christos Boutsidis, Petros Drineas, and Malik Magdon-Ismail · 2013
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Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering
Dan Feldman, Melanie Schmidt, and Christian Sohler · 2013
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Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering
Dan Feldman, Melanie Schmidt, and Christian Sohler · 2013
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Improving cur matrix decomposition and the nyström approximation via adaptive sampling
Shusen Wang and Zhihua Zhang · 2013
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Sérgio Moro, Paulo Cortez, and Paulo Rita · 2014
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Ryan R Curtin, Sungjin Im, Ben Moseley, Kirk Pruhs, and Alireza Samadian · 2019
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Fast and accurate least-mean-squares solvers
Alaa Maalouf, Ibrahim Jubran, and Dan Feldman · 2019
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Core-sets: Updated survey
Dan Feldman · 2020
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Unconditional coresets for regularized loss minimization
Alireza Samadian, Kirk Pruhs, Benjamin Moseley, Sungjin Im, and Ryan Curtin · 2020
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Coresets for near-convex functions
Morad Tukan, Alaa Maalouf, and Dan Feldman · 2020
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Open source code for all the algorithms presented in this paper, 2021
Code · 2021
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Coresets for classification–simplified and strengthened
Tung Mai, Anup B Rao, and Cameron Musco · 2021
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On coresets for support vector machines
Murad Tukan, Cenk Baykal, Dan Feldman, and Daniela Rus · 2021
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