Azken berriak

Ikusi guztiak

Zentroari buruz

Matematika tailerrak eta bakarrizketak izango dira 2024ko BCAM Naukaseko protagonistak

  • BCAM eta Euskal Herriko Unibertsitateko Kultura Zientifikoko Katedrak martxoaren 14rako goiz eta arratsalderako egitaraua antolatu dute.

Zentroari buruz

Teknologia Kuantikoei buruzko IKUR hitzaldiak Artur Ekert irakaslearekin (Donostia, Martxoaren 7 / Bilbo, Martxoaren 8)

  • IKUR hitzaldi kuantikoak Donostia International Physics Center (DIPC), Euskal Herriko Unibertsitatea (UPV/EHU) eta Basque Center for Applied Mathematics (BCAM) erakundeek a

Zentroari buruz

BCAMek eta Deustuko Unibertsitateak hitzarmen bat sinatu dute matematiketan lankidetza akademikoa eta zientifikoa sustatzeko

  • Bi erakundeen arteko loturak sendotzen dituen akordio honen helburu nagusia ikerketa sustatzea da, oro har matematik

BCAM pertsonak

Iñigo Urteaga, BCAMeko Ikerbasque Research Fellow, Ameriketako Estatu Batuetako National Science Foundationeko ikerketa-proiektu bateko ikertzaile nagusia izango da datozen 4 urteetan

  • Proiektua 'Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)' programak finantzatzen du 

Azken argitalpenak

Ikusi guztiak

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...