Marco Capó

According to our database, Marco Capó authored at least 12 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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, Garth Cruickshank, Bipin Patel

NeuroImage, 2025

2024

Fast $K$-Medoids With the $l_{1}$-Norm.

Marco Capó, Aritz Pérez, José Antonio Lozano

IEEE Trans. Artif. Intell., April, 2024

2023

LASSO for streaming data with adaptative filtering.

Marco Capó, Aritz Pérez, José Antonio Lozano

Stat. Comput., 2023

Fast computation of cluster validity measures for bregman divergences and benefits.

Marco Capó, Aritz Pérez, José Antonio Lozano

Pattern Recognit. Lett., 2023

2022

An Efficient Split-Merge Re-Start for the $K$K-Means Algorithm.

Marco Capó, Aritz Pérez, José Antonio Lozano

IEEE Trans. Knowl. Data Eng., 2022

2021

A Cheap Feature Selection Approach for the K-Means Algorithm.

Marco Capó, Aritz Pérez, José Antonio Lozano

IEEE Trans. Neural Networks Learn. Syst., 2021

K-means for Evolving Data Streams.

Arkaitz Bidaurrazaga, Aritz Pérez, Marco Capó

Proceedings of the IEEE International Conference on Data Mining, 2021

2020

An efficient K-means clustering algorithm for tall data.

Marco Capó, Aritz Pérez, José Antonio Lozano

Data Min. Knowl. Discov., 2020

Passive Approach for the K-means Problem on Streaming Data.

Arkaitz Bidaurrazaga, Aritz Pérez, Marco Capó

CoRR, 2020

2018

An efficient K -means clustering algorithm for massive data.

Marco Capó, Aritz Pérez, José Antonio Lozano

CoRR, 2018

2017

An efficient approximation to the K-means clustering for massive data.

Marco Capó, Aritz Pérez, José Antonio Lozano

Knowl. Based Syst., 2017

2016

An efficient K-means algorithm for Massive Data.

Marco Capó, Aritz Pérez, José Antonio Lozano

CoRR, 2016