Latest news

View all

About the center, BCAM people

Nine new PhD students joined BCAM the last year

Basque Center for Applied Mathematics – BCAM has welcomed to the center a new group of PhD students for the course 2023-2024 and they have joined the rest students, who number 9 in total.

About the center

Mathematical workshops and monologues will star BCAM Naukas 2024

  • BCAM and the Chair of Scientific Culture at the University of the Basque Country have organized a program of activities for both morning and afternoon of March 14th.

About the center

IN-DEEP, an MSCA Doctoral Network project aimed at training doctoral students in Deep Learning techniques, kicks off

  • The initial meeting (Kick Off meeting) took place on February 1st.

About the center

IKUR talks on Quantum Technologies with Professor Artur Ekert (Donostia, March 7th / Bilbao, March 8th)

  • The IKUR Quantum Talks are organized by the Donostia International Physics Center (DIPC), the University of the Basque Country (UPV/EHU) and the Basque Center for App

Latest publications

View all

Speeding-Up Evolutionary Algorithms to Solve Black-Box Optimization Problems

Echevarrieta, J.; Arza, E.; Pérez, A. (2024-01-10)

Population-based evolutionary algorithms are often considered when approaching computationally expensive black-box optimization problems. They employ a selection mechanism to choose the best solutions from a given population...

Fast Computation of Cluster Validity Measures for Bregman Divergences and Benefits

Capó, M.; Pérez, A.; Lozano, J.A. (2023-01-01)

Partitional clustering is one of the most relevant unsupervised learning and pattern recognition techniques. Unfortunately, one of the main drawbacks of these methodologies refer to the fact that the number of clusters is ge...

Fast K-Medoids With the l_1-Norm

Capó, M.; Pérez, A.; Lozano, J.A. (2023-07-26)

K-medoids clustering is one of the most popular techniques in exploratory data analysis. The most commonly used algorithms to deal with this problem are quadratic on the number of instances, n, and usually the quality of the...

Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees

Álvarez, V.; Mazuelas, S.; Lozano, J.A. (2023-12-01)

For a sequence of classification tasks that arrive over time, it is common that tasks are evolving in the sense that consecutive tasks often have a higher similarity. The incremental learning of a growing sequence of tasks...