Publications (13)

¹ Publicaciones consideradas como producción de la unidad.

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in the year 2024 Remove filter
filter_list from 2024 to 2024 Distributed, Parallel, and Cluster Computing

2024

  1. A Distributed Particle Swarm Optimization Algorithm Based on Apache Spark for Asynchronous Parallel Training of Deep Neural Networks

    ACM International Conference Proceeding Series

  2. CPU and GPU oriented optimizations for LiDAR data processing

    Journal of Computational Science, Vol. 79

  3. Continuous QoS-compliant orchestration in the Cloud-Edge continuum

    Software - Practice and Experience, Vol. 54, Núm. 11, pp. 2191-2213

  4. Exploring multiprocessor approaches to time series analysis

    Journal of Parallel and Distributed Computing, Vol. 188

  5. Federated Learning Meets Blockchain: A Kafka-ML Integration for reliable model training using data streams

    Proceedings - 2024 IEEE International Conference on Big Data, BigData 2024

  6. Federated cloud-native service placement in latency-sensitive and resource-constrained scenarios

    Proceedings - 2024 IEEE World Forum on Public Safety Technology, WFPST 2024

  7. Functions as a service for distributed deep neural network inference over the cloud-to-things continuum

    Software - Practice and Experience, Vol. 54, Núm. 8, pp. 1297-1311

  8. Online learning and continuous model upgrading with data streams through the Kafka-ML framework

    Future Generation Computer Systems, Vol. 160, pp. 251-263

  9. Parallel PSO for Efficient Neural Network Training Using GPGPU and Apache Spark in Edge Computing Sets

    Algorithms, Vol. 17, Núm. 9

  10. Parallel-Distributed Implementation of the Lipizzaner Framework for Multiobjective Coevolutionary Training of Generative Adversarial Networks

    Communications in Computer and Information Science

  11. Programming Open Distributed Systems in Maude

    ACM International Conference Proceeding Series

  12. The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka-ML: A deep-learning performance comparative

    Expert Systems, Vol. 41, Núm. 2

  13. Towards flexible data stream collaboration: Federated Learning in Kafka-ML

    Internet of Things (Netherlands), Vol. 25