ListarGI-LIDIA - Artigos por tema "Edge computing"

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    • Fast deep autoencoder for federated learning 

      Novoa-Paradela, David; Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha (Elsevier Ltd, 2023-11)
      [Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...

    • FedHEONN: Federated and homomorphically encrypted learning method for one-layer neural networks 

      Fontenla-Romero, Óscar; Guijarro-Berdiñas, Bertha; Hernández-Pereira, Elena; Pérez-Sánchez, Beatriz (Elsevier B.V., 2023)
      [Abstract]: Federated learning (FL) is a distributed approach to developing collaborative learning models from decentralized data. This is relevant to many real applications, such as in the field of the Internet of Things, ...

    • Low-Precision Feature Selection on Microarray Data: An Information Theoretic Approach 

      Morán-Fernández, Laura; Bolón-Canedo, Verónica; Alonso-Betanzos, Amparo (Springer, 2022)
      [Abstract] The number of interconnected devices, such as personal wearables, cars, and smart-homes, surrounding us every day has recently increased. The Internet of Things devices monitor many processes, and have the ...