Zobrazeno 1 - 10
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pro vyhledávání: '"Veiga AS"'
Autor:
Fernández-Piñeiro, Pablo, Ferández-Veiga, Manuel, Díaz-Redondo, Rebeca P., Fernández-Vilas, Ana, González-Soto, Martín
In prototype-based federated learning, the exchange of model parameters between clients and the master server is replaced by transmission of prototypes or quantized versions of the data samples to the aggregation server. A fully decentralized deploym
Externí odkaz:
http://arxiv.org/abs/2411.09267
We study the problem of stock replenishment and transshipment in the retail industry. We develop a model that can accommodate different policies, including centralized redistribution (replenishment) and decentralized redistribution (lateral transship
Externí odkaz:
http://arxiv.org/abs/2410.18571
In computational physics, machine learning has now emerged as a powerful complementary tool to explore efficiently candidate designs in engineering studies. Outputs in such supervised problems are signals defined on meshes, and a natural question is
Externí odkaz:
http://arxiv.org/abs/2410.15721
We carry out a stability and convergence analysis for the fully discrete scheme obtained by combining a finite or virtual element spatial discretization with the upwind-discontinuous Galerkin time-stepping applied to the time-dependent advection-diff
Externí odkaz:
http://arxiv.org/abs/2410.13635
Autor:
Castro, David Pérez, Vilas, Ana Fernández, Fernández-Veiga, Manuel, Rodríguez, Mateo Blanco, Redondo, Rebeca P. Díaz
We implement a simulation environment on top of NetSquid that is specifically designed for estimating the end-to-end fidelity across a path of quantum repeaters or quantum switches. The switch model includes several generalizations which are not curr
Externí odkaz:
http://arxiv.org/abs/2410.09779
The impacts of climate change are intensifying existing vulnerabilities and disparities within urban communities around the globe, as extreme weather events, including floods and heatwaves, are becoming more frequent and severe, disproportionately af
Externí odkaz:
http://arxiv.org/abs/2410.04318
Autor:
Silva, A. G., Pontes, R. B., Boldrin, M., Pessoni, H. V. S., Veiga, L. S. I., Jesus, J. R., Fabrelli, H., Gonzaga, A. R. C., Bittar, E. M., Bufaiçal, L.
Publikováno v:
Physical Review B 110, 144415 (2024)
The electron spin polarization on half-metallic double-perovskites is usually conditioned to the ordered rock-salt arrangement of the transition-metal ions along the lattice. In this work, we investigate a polycrystalline sample of the Ca1.5La0.5MnRu
Externí odkaz:
http://arxiv.org/abs/2410.01980
Autor:
Cajaraville-Aboy, Diego, Fernández-Vilas, Ana, Díaz-Redondo, Rebeca P., Fernández-Veiga, Manuel
Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) extends the FL paradigm by eliminating the central server, the
Externí odkaz:
http://arxiv.org/abs/2409.17754
In this work we design a novel $C^1$-conforming virtual element method of arbitrary order $k \geq 2$, to solve the biharmonic problem on a domain with curved boundary and internal curved interfaces in two dimensions. By introducing a suitable stabili
Externí odkaz:
http://arxiv.org/abs/2408.17381
Autor:
Moreira, Gustavo, Hosseini, Maryam, Veiga, Carolina, Alexandre, Lucas, Colaninno, Nicola, de Oliveira, Daniel, Ferreira, Nivan, Lage, Marcos, Miranda, Fabio
Over the past decade, several urban visual analytics systems and tools have been proposed to tackle a host of challenges faced by cities, in areas as diverse as transportation, weather, and real estate. Many of these tools have been designed through
Externí odkaz:
http://arxiv.org/abs/2408.06139