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Alaa Maalouf
Researcher at University of Haifa
Publications - 30
Citations - 188
Alaa Maalouf is an academic researcher from University of Haifa. The author has contributed to research in topics: Computer science & Coreset. The author has an hindex of 6, co-authored 21 publications receiving 115 citations.
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Proceedings Article
Fast and Accurate Least-Mean-Squares Solvers
TL;DR: An algorithm that gets a finite set of n d-dimensional real vectors and returns a subset of d+1 vectors with positive weights whose weighted sum is \emph{exactly} the same, based on a novel paradigm of fusion between different data summarization techniques, known as sketches and coresets.
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Fast and Accurate Least-Mean-Squares Solvers
TL;DR: In this paper, the authors proposed a faster algorithm that computes a weighted subset of sparsified input points in O(nd+d^4\log{n}) time, using O(log n)$ calls to Caratheodory's construction on small but "smart" subsets.
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Coresets for Near-Convex Functions.
TL;DR: A generic framework for computing sensitivities (and thus coresets) for wide family of loss functions which the authors call near-convex functions is suggested by suggesting the $f-SVD factorization that generalizes the SVDfactorization of matrices to functions.
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Introduction to Coresets: Accurate Coresets.
TL;DR: This introductory paper was written following requests from (usually non-expert, but also colleagues) regarding the many inconsistent coreset definitions, lack of available source code, the required deep theoretical background from different fields, and the dense papers that make it hard for beginners to apply coresets and develop new ones.
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Tight Sensitivity Bounds For Smaller Coresets
TL;DR: Experimental results on real-world datasets, including the English Wikipedia documents-term matrix, show that the bounds provided provide significantly smaller and data-dependent coresets also in practice.