Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Beltrán, Enrique Tomás Martínez"'
Autor:
Feng, Chao, Celdrán, Alberto Huertas, von der Assen, Jan, Beltrán, Enrique Tomás Martínez, Bovet, Gérôme, Stiller, Burkhard
Federated Learning (FL) has emerged as a promising approach to address privacy concerns inherent in Machine Learning (ML) practices. However, conventional FL methods, particularly those following the Centralized FL (CFL) paradigm, utilize a central s
Externí odkaz:
http://arxiv.org/abs/2407.08652
Autor:
Feng, Chao, Celdrán, Alberto Huertas, Baltensperger, Janosch, Beltrán, Enrique Tomás Martínez, Sánchez, Pedro Miguel Sánchez, Bovet, Gérôme, Stiller, Burkhard
Decentralized Federated Learning (DFL) emerges as an innovative paradigm to train collaborative models, addressing the single point of failure limitation. However, the security and trustworthiness of FL and DFL are compromised by poisoning attacks, n
Externí odkaz:
http://arxiv.org/abs/2310.08097
Autor:
Gómez, Ángel Luis Perales, Beltrán, Enrique Tomás Martínez, Sánchez, Pedro Miguel Sánchez, Celdrán, Alberto Huertas
Industry 4.0 has brought numerous advantages, such as increasing productivity through automation. However, it also presents major cybersecurity issues such as cyberattacks affecting industrial processes. Federated Learning (FL) combined with time-ser
Externí odkaz:
http://arxiv.org/abs/2308.03554
Autor:
Beltrán, Enrique Tomás Martínez, Sánchez, Pedro Miguel Sánchez, Bernal, Sergio López, Bovet, Gérôme, Pérez, Manuel Gil, Pérez, Gregorio Martínez, Celdrán, Alberto Huertas
The rise of Decentralized Federated Learning (DFL) has enabled the training of machine learning models across federated participants, fostering decentralized model aggregation and reducing dependence on a server. However, this approach introduces uni
Externí odkaz:
http://arxiv.org/abs/2307.11730
Autor:
Beltrán, Enrique Tomás Martínez, Gómez, Ángel Luis Perales, Feng, Chao, Sánchez, Pedro Miguel Sánchez, Bernal, Sergio López, Bovet, Gérôme, Pérez, Manuel Gil, Pérez, Gregorio Martínez, Celdrán, Alberto Huertas
In 2016, Google proposed Federated Learning (FL) as a novel paradigm to train Machine Learning (ML) models across the participants of a federation while preserving data privacy. Since its birth, Centralized FL (CFL) has been the most used approach, w
Externí odkaz:
http://arxiv.org/abs/2306.09750
Autor:
Bernal, Sergio López, Pérez, Mario Quiles, Beltrán, Enrique Tomás Martínez, Pérez, Gregorio Martínez, Celdrán, Alberto Huertas
The metaverse has gained tremendous popularity in recent years, allowing the interconnection of users worldwide. However, current systems in metaverse scenarios, such as virtual reality glasses, offer a partial immersive experience. In this context,
Externí odkaz:
http://arxiv.org/abs/2212.03169
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges
Autor:
Beltrán, Enrique Tomás Martínez, Pérez, Mario Quiles, Sánchez, Pedro Miguel Sánchez, Bernal, Sergio López, Bovet, Gérôme, Pérez, Manuel Gil, Pérez, Gregorio Martínez, Celdrán, Alberto Huertas
In recent years, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the most common approach in the literature, where a central entity creates a
Externí odkaz:
http://arxiv.org/abs/2211.08413
Autor:
Sánchez, Pedro Miguel Sánchez, Celdrán, Alberto Huertas, Beltrán, Enrique Tomás Martínez, Demeter, Daniel, Bovet, Gérôme, Pérez, Gregorio Martínez, Stiller, Burkhard
Federated learning (FL) allows participants to collaboratively train machine and deep learning models while protecting data privacy. However, the FL paradigm still presents drawbacks affecting its trustworthiness since malicious participants could la
Externí odkaz:
http://arxiv.org/abs/2210.11061
Autor:
Rogel, José Manuel Hidalgo, Beltrán, Enrique Tomás Martínez, Pérez, Mario Quiles, Bernal, Sergio López, Pérez, Gregorio Martínez, Celdrán, Alberto Huertas
- Background / Introduction: Driver drowsiness is a significant concern and one of the leading causes of traffic accidents. Advances in cognitive neuroscience and computer science have enabled the detection of drivers' drowsiness using Brain-Computer
Externí odkaz:
http://arxiv.org/abs/2209.04048
Autor:
Pérez, Mario Quiles, Beltrán, Enrique Tomás Martínez, Bernal, Sergio López, Prat, Eduardo Horna, Del Campo, Luis Montesano, Maimó, Lorenzo Fernández, Celdrán, Alberto Huertas
The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater acceptance on pote
Externí odkaz:
http://arxiv.org/abs/2209.00993