21 citations · 21 across the 4 of their papers we have counts for
5 papers
Acceleration of Parallel Tempering for Markov Chain Monte Carlo methods
Aingeru Ramos, Jose A Pascual, Javier Navaridas +1
Markov Chain Monte Carlo methods are algorithms used to sample probability distributions, commonly used to sample the Boltzmann distribution of physical/chemical models (e.g., prot…
On the Convergence of Markov Chain Distribution within Quantum Walk Circuit Subspace
Aingeru Ramos, Jose A. Pascual, Javier Navaridas +1
Markov Chain Monte Carlo (MCMC) methods are algorithms for sampling probability distributions, commonly applied to the Boltzmann distribution in physical and chemical models such a…
GLow -- A Novel, Flower-Based Simulated Gossip Learning Strategy
Aitor Belenguer, Jose A. Pascual, Javier Navaridas
Fully decentralized learning algorithms are still in an early stage of development. Creating modular Gossip Learning strategies is not trivial due to convergence challenges and Byz…
GowFed -- A novel Federated Network Intrusion Detection System
Aitor Belenguer, Jose A. Pascual, Javier Navaridas
Network intrusion detection systems are evolving into intelligent systems that perform data analysis while searching for anomalies in their environment. Indeed, the development of…
A review of Federated Learning in Intrusion Detection Systems for IoT
Aitor Belenguer, Javier Navaridas, Jose A. Pascual
Intrusion detection systems are evolving into intelligent systems that perform data analysis searching for anomalies in their environment. The development of deep learning technolo…