An efficient K-means algorithm for Massive Data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (CoRR, 2016)

An efficient approximation to the K-means clustering for massive data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Knowl. Based Syst., 2017)

An efficient K -means clustering algorithm for massive data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (CoRR, 2018)

Passive Approach for the K-means Problem on Streaming Data. - Arkaitz Bidaurrazaga; Aritz Pérez; Marco Capó (CoRR, 2020)

An efficient K-means clustering algorithm for tall data. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Data Min. Knowl. Discov., 2020)

K-means for Evolving Data Streams. - Arkaitz Bidaurrazaga; Aritz Pérez; Marco Capó (ICDM, 2021)

A Cheap Feature Selection Approach for the K-Means Algorithm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Neural Networks Learn. Syst., 2021)

An Efficient Split-Merge Re-Start for the $K$K-Means Algorithm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Knowl. Data Eng., 2022)

Fast computation of cluster validity measures for bregman divergences and benefits. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Pattern Recognit. Lett., 2023)

LASSO for streaming data with adaptative filtering. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (Stat. Comput., 2023)

Fast $K$-Medoids With the $l_{1}$-Norm. - Marco Capó; Aritz Pérez; José Antonio Lozano 001 (IEEE Trans. Artif. Intell., 2024)

UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases. - Marco Capó; Silvia Vitali; Georgios Athanasiou; Nicole Cusimano; Daniel García 002; Garth Cruickshank; Bipin Patel (NeuroImage, 2025)