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Maximilian Vötsch

2 accepted papers

2023

Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization

ICML 2023poster

We introduce efficient $(1+\varepsilon)$-approximation algorithms for the binary matrix factorization (BMF) problem, where the inputs are a matrix $\mathbf{A}\in\{0,1\}^{n\times d}$, a rank parameter $k>0$, as well as an accuracy parameter $\varepsilon>0$, and the goal is to approximate $\mathbf{A}$…

Cited by 0SourcePDFScholar
2023

Simple, Scalable and Effective Clustering via One-Dimensional Projections

NeurIPS 2023poster

Clustering is a fundamental problem in unsupervised machine learning with many applications in data analysis. Popular clustering algorithms such as Lloyd's algorithm and $k$-means++ can take $\Omega(ndk)$ time when clustering $n$ points in a $d$-dimensional space (represented by an $n\times d$ matri…

Cited by 3SourcePDFScholar