81 citations · 340 across the 21 of their papers we have counts for
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Randomized Dimensionality Reduction for k-means Clustering
Christos Boutsidis, Anastasios Zouzias, Michael W. Mahoney +1
We study the topic of dimensionality reduction for -means clustering. Dimensionality reduction encompasses the union of two approaches: \emph{feature selection} and \emph{featur…
Deterministic Feature Selection for -means Clustering
Christos Boutsidis, Malik Magdon-Ismail
We study feature selection for -means clustering. Although the literature contains many methods with good empirical performance, algorithms with provable theoretical behavior ha…
Topics in Matrix Sampling Algorithms
Christos Boutsidis
We study three fundamental problems of Linear Algebra, lying in the heart of various Machine Learning applications, namely: 1)"Low-rank Column-based Matrix Approximation". We are g…
Improved Low-rank Matrix Decompositions via the Subsampled Randomized Hadamard Transform
Christos Boutsidis
We comment on two randomized algorithms for constructing low-rank matrix decompositions. Both algorithms employ the Subsampled Randomized Hadamard Transform [14]. The first algorit…
Near-Optimal Column-Based Matrix Reconstruction
Christos Boutsidis, Petros Drineas, Malik Magdon-Ismail
We consider low-rank reconstruction of a matrix using its columns and we present asymptotically optimal algorithms for both spectral norm and Frobenius norm reconstruction. The mai…