NPEPE: Massive Natural Computing Engine for Optimally Solving NP-complete Problems in Big Data Scenarios. - Sandra Gómez Canaval; Bruno Ordozgoiti Rubio; Alberto Mozo (ADBIS (Short Papers and Workshops), 2015)

Massively Parallel Unsupervised Feature Selection on Spark. - Bruno Ordozgoiti Rubio; Sandra Gómez Canaval; Alberto Mozo (ADBIS (Short Papers and Workshops), 2015)

Feature Ranking and Selection for Big Data Sets. - Bruno Ordozgoiti Rubio; Sandra Gómez Canaval; Alberto Mozo (ADBIS (Short Papers and Workshops), 2016)

Parallelized unsupervised feature selection for large-scale network traffic analysis. - Bruno Ordozgoiti; Sandra Gómez Canaval; Alberto Mozo (ESANN, 2016)

PSCEG: an unbiased parallel subspace clustering algorithm using exact grids. - Bo Zhu 008; Alberto Mozo; Bruno Ordozgoiti (ESANN, 2016)

CogNet: A network management architecture featuring cognitive capabilities. - Lei Xu; Haytham Assem; Imen Grida Ben Yahia; Teodora Sandra Buda; Ángel Martín; Domenico Gallico; Matteo Biancani; Antonio Pastor 001; Pedro A. Aranda; Mikhail I. Smirnov; Danny Raz; Olga Uryupina; et al. (EuCNC, 2016)

A Fast Iterative Algorithm for Improved Unsupervised Feature Selection. - Bruno Ordozgoiti Rubio; Sandra Gómez Canaval; Alberto Mozo (ICDM, 2016)

Can machine learning aid in delivering new use cases and scenarios in 5G? - Teodora Sandra Buda; Haytham Assem; Lei Xu; Danny Raz; Udi Margolin; Elisha J. Rosensweig; Diego R. López; Marius Iulian Corici; Mikhail Smirnov; Robert Mullins; Olga Uryupina; Alberto Mozo; et al. (NOMS, 2016)

Using Machine Learning to Detect Noisy Neighbors in 5G Networks. - Udi Margolin; Alberto Mozo; Bruno Ordozgoiti Rubio; Danny Raz; Elisha J. Rosensweig; Itai Segall (CoRR, 2016)

Deep convolutional neural networks for detecting noisy neighbours in cloud infrastructure. - Bruno Ordozgoiti; Alberto Mozo; Sandra Gómez Canaval; Udi Margolin; Elisha J. Rosensweig; Itai Segall (ESANN, 2017)

Probabilistic Leverage Scores for Parallelized Unsupervised Feature Selection. - Bruno Ordozgoiti Rubio; Sandra Gómez Canaval; Alberto Mozo (IWANN (2), 2017)

Iterative column subset selection. - Bruno Ordozgoiti Rubio; Sandra Gómez Canaval; Alberto Mozo (Knowl. Inf. Syst., 2018)

Column subset selection in practice : efficient heuristics and regularization. - Bruno Ordozgoiti Rubio (2018)

Discovering Polarized Communities in Signed Networks. - Francesco Bonchi; Edoardo Galimberti; Aristides Gionis; Bruno Ordozgoiti; Giancarlo Ruffo (CIKM, 2019)

Reconciliation k-median: Clustering with Non-polarized Representatives. - Bruno Ordozgoiti; Aristides Gionis (WWW, 2019)

Regularized greedy column subset selection. - Bruno Ordozgoiti; Alberto Mozo; Jesús García López de Lacalle (Inf. Sci., 2019)

Discovering conflicting groups in signed networks. - Ruo-Chun Tzeng; Bruno Ordozgoiti; Aristides Gionis (NeurIPS, 2020)

Off-the-Grid: Fast and Effective Hyperparameter Search for Kernel Clustering. - Bruno Ordozgoiti; Lluís A. Belanche Muñoz (ECML/PKDD (2), 2020)

Mining Signed Networks: Theory and Applications: Tutorial proposal for the Web Conference 2020. - Aristides Gionis; Antonis Matakos; Bruno Ordozgoiti; Han Xiao 009 (WWW (Companion Volume), 2020)

Finding large balanced subgraphs in signed networks. - Bruno Ordozgoiti; Antonis Matakos; Aristides Gionis (WWW, 2020)

Searching for polarization in signed graphs: a local spectral approach. - Han Xiao 009; Bruno Ordozgoiti; Aristides Gionis (WWW, 2020)

Diversity-Aware k-median: Clustering with Fair Center Representation. - Suhas Thejaswi; Bruno Ordozgoiti; Aristides Gionis (ECML/PKDD (2), 2021)

Insightful Dimensionality Reduction with Very Low Rank Variable Subsets. - Bruno Ordozgoiti; Sachith Pai; Marta Kolczynska (WWW, 2021)

Approximation algorithms for k-median with lower-bound constraints. - Ameet Gadekar; Bruno Ordozgoiti; Suhas Thejaswi (CoRR, 2021)

Generalized Leverage Scores: Geometric Interpretation and Applications. - Bruno Ordozgoiti; Antonis Matakos; Aristides Gionis (ICML, 2022)

Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics. - Suhas Thejaswi; Ameet Gadekar; Bruno Ordozgoiti; Michal Osadnik (KDD, 2022)

Accepted Tutorials at The Web Conference 2022. - Riccardo Tommasini 001; Senjuti Basu Roy; Xuan Wang 008; Hongwei Wang; Heng Ji 001; Jiawei Han 001; Preslav Nakov; Giovanni Da San Martino; Firoj Alam; Markus Schedl; Elisabeth Lex; Akash Bharadwaj; et al. (WWW (Companion Volume), 2022)

Provable randomized rounding for minimum-similarity diversification. - Bruno Ordozgoiti; Ananth Mahadevan; Antonis Matakos; Aristides Gionis (Data Min. Knowl. Discov., 2022)

A Constant-Factor Approximation Algorithm for Reconciliation k-Median. - Joachim Spoerhase; Kamyar Khodamoradi; Benedikt Riegel; Bruno Ordozgoiti; Aristides Gionis (AISTATS, 2023)

Fair Column Subset Selection. - Antonis Matakos; Bruno Ordozgoiti; Suhas Thejaswi (KDD, 2024)

Diversity-aware clustering: Computational Complexity and Approximation Algorithms. - Suhas Thejaswi; Ameet Gadekar; Bruno Ordozgoiti; Aristides Gionis (CoRR, 2024)