81 citations · 340 across the 21 of their papers we have counts for
4 papers · 1 filter
Optimal Principal Component Analysis in Distributed and Streaming Models
Christos Boutsidis, David P. Woodruff, Peilin Zhong
We study the Principal Component Analysis (PCA) problem in the distributed and streaming models of computation. Given a matrix a rank parameter $k < rank(A)…
A Randomized Algorithm for Approximating the Log Determinant of a Symmetric Positive Definite Matrix
Christos Boutsidis, Petros Drineas, Prabhanjan Kambadur +2
We introduce a novel algorithm for approximating the logarithm of the determinant of a symmetric positive definite (SPD) matrix. The algorithm is randomized and approximates the tr…
Optimal Sparse Linear Auto-Encoders and Sparse PCA
Malik Magdon-Ismail, Christos Boutsidis
Principal components analysis (PCA) is the optimal linear auto-encoder of data, and it is often used to construct features. Enforcing sparsity on the principal components can promo…
Greedy Minimization of Weakly Supermodular Set Functions
Christos Boutsidis, Edo Liberty, Maxim Sviridenko
This paper defines weak--supermodularity for set functions. Many optimization objectives in machine learning and data mining seek to minimize such functions under cardinality co…