15 citations · 44 across the 12 of their papers we have counts for
11 papers
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…
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…
Provably Approximated ICP
Ibrahim Jubran, Alaa Maalouf, Ron Kimmel +1
The goal of the \emph{alignment problem} is to align a (given) point cloud to another (observed) point cloud . That is, to compute…
Deep Learning Meets Projective Clustering
Alaa Maalouf, Harry Lang, Daniela Rus +1
A common approach for compressing NLP networks is to encode the embedding layer as a matrix , compute its rank- approximation via SVD, and then…
Compressed Deep Networks: Goodbye SVD, Hello Robust Low-Rank Approximation
Murad Tukan, Alaa Maalouf, Matan Weksler +1
A common technique for compressing a neural network is to compute the -rank approximation of the matrix that corresponds to a ful…
Coresets for Near-Convex Functions
Murad Tukan, Alaa Maalouf, Dan Feldman
Coreset is usually a small weighted subset of input points in , that provably approximates their loss function for a given set of queries (models, classifiers, et…