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20152022
most citedDimensionality Reduction of Massive Sparse Datasets Using Coresets

34 citations · 89 across the 21 of their papers we have counts for

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cs.LG2022

New Coresets for Projective Clustering and Applications

Murad Tukan, Xuan Wu, Samson Zhou +2

-projective clustering is the natural generalization of the family of -clustering and -subspace clustering problems. Given a set of points in , the g…

cs.LG2022

Coresets for Data Discretization and Sine Wave Fitting

Alaa Maalouf, Murad Tukan, Eric Price +2

In the \emph{monitoring} problem, the input is an unbounded stream of integers in , that are obtained from a sensor (such as GPS or heart b…

cs.LG2021

Introduction to Coresets: Approximated Mean

Alaa Maalouf, Ibrahim Jubran, Dan Feldman

A \emph{strong coreset} for the mean queries of a set in is a small weighted subset , which provably approximates its sum of squared distances to…

cs.LG20211 cited

A Unified Approach to Coreset Learning

Alaa Maalouf, Gilad Eini, Ben Mussay +2

Coreset of a given dataset and loss function is usually a small weighed set that approximates this loss for every query from a given set of queries. Coresets have shown to be very…

cs.LG20211 cited

Coresets for Decision Trees of Signals

Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman +1

A -decision tree (or -tree) is a recursive partition of a matrix (2D-signal) into block matrices (axis-parallel rectangles, leaves) where each rectangle is assi…

cs.LG2020

Introduction to Core-sets: an Updated Survey

Dan Feldman

In optimization or machine learning problems we are given a set of items, usually points in some metric space, and the goal is to minimize or maximize an objective function over so…