no code implementations • 10 Jan 2024 • Suhas Thejaswi, Ameet Gadekar, Bruno Ordozgoiti, Aristides Gionis

We present parameterized approximation algorithms with approximation ratios $1+ \frac{2}{e}$, $1+\frac{8}{e}$ and $3$ for diversity-aware $k$-median, diversity-aware $k$-means and diversity-aware $k$-supplier, respectively.

1 code implementation • 7 Jun 2023 • Antonis Matakos, Bruno Ordozgoiti, Suhas Thejaswi

The problem of column subset selection asks for a subset of columns from an input matrix such that the matrix can be reconstructed as accurately as possible within the span of the selected columns.

no code implementations • 16 Jun 2022 • Bruno Ordozgoiti, Antonis Matakos, Aristides Gionis

In particular, leverage scores, which relate the columns of a matrix to the subspaces spanned by its leading singular vectors, are helpful in revealing column subsets to approximately factorize a matrix with quality guarantees.

1 code implementation • NeurIPS 2020 • Ruo-Chun Tzeng, Bruno Ordozgoiti, Aristides Gionis

In this paper we study the problem of detecting $k$ conflicting groups in a signed network.

1 code implementation • 24 Jun 2020 • Bruno Ordozgoiti, Lluís A. Belanche Muñoz

In this paper we study the impact of kernel parameters on kernel $k$-means.

1 code implementation • 26 Jan 2020 • Han Xiao, Bruno Ordozgoiti, Aristides Gionis

In this paper we formulate the problem of finding local polarized communities in signed graphs as a locally-biased eigen-problem.

no code implementations • 12 Apr 2018 • Bruno Ordozgoiti, Alberto Mozo, Jesús García López de Lacalle

The Column Subset Selection Problem provides a natural framework for unsupervised feature selection.

no code implementations • 24 Oct 2016 • Udi Margolin, Alberto Mozo, Bruno Ordozgoiti, Danny Raz, Elisha Rosensweig, Itai Segall

5G networks are expected to be more dynamic and chaotic in their structure than current networks.

Cannot find the paper you are looking for? You can
Submit a new open access paper.

Contact us on:
hello@paperswithcode.com
.
Papers With Code is a free resource with all data licensed under CC-BY-SA.