Real-world machine learning systems: A survey from a data-oriented architecture perspective
Machine Learning models are being deployed as parts of real-world systems with the
upsurge of interest in artificial intelligence. The design, implementation, and maintenance of …
upsurge of interest in artificial intelligence. The design, implementation, and maintenance of …
The Hexa-X project vision on Artificial Intelligence and Machine Learning-driven Communication and Computation co-design for 6G
This paper provides an overview of the most recent advancements and outcomes of the
European 6G flagship project Hexa-X, on the topic of in-network Artificial Intelligence (AI) …
European 6G flagship project Hexa-X, on the topic of in-network Artificial Intelligence (AI) …
[HTML][HTML] A value-oriented Artificial Intelligence-as-a-Service business plan using integrated tools and services
The latest developments in Artificial Intelligence (AI) are the focal point in increasing the
performance of other technologies and the evolution of Industry 4.0. Considering the …
performance of other technologies and the evolution of Industry 4.0. Considering the …
Continual adaptation of federated reservoirs in pervasive environments
When performing learning tasks in pervasive environments, the main challenge arises from
the need of combining federated and continual settings. The former comes from the massive …
the need of combining federated and continual settings. The former comes from the massive …
E-Navigation: A Distributed Decision Support System With Extended Reality for Bridge and Ashore Seafarers
A distributed decision support system has been developed to assist seafarers during several
navigation tasks, for instance, in avoiding a collision with a detected obstacle in the sea and …
navigation tasks, for instance, in avoiding a collision with a detected obstacle in the sea and …
A novel approach to distributed model aggregation using apache kafka
Multi-Access Edge Computing (MEC) is attracting a lot of interest because it complements
cloud-based approaches. Indeed, MEC is opening up in the direction of reducing both …
cloud-based approaches. Indeed, MEC is opening up in the direction of reducing both …
Federated adaptation of reservoirs via intrinsic plasticity
We propose a novel algorithm for performing federated learning with Echo State Networks
(ESNs) in a client-server scenario. In particular, our proposal focuses on the adaptation of …
(ESNs) in a client-server scenario. In particular, our proposal focuses on the adaptation of …
Prediction of driver's stress affection in simulated autonomous driving scenarios
We investigate the task of predicting stress affection from physiological data of users
experiencing simulations of autonomous driving. We approach this task on two levels of …
experiencing simulations of autonomous driving. We approach this task on two levels of …
TEACHING Platform for Human-Centric Autonomous Applications: Design and Overview
The TEACHING project enhances AI applications in pervasive environments via Humanistic
Intelligence, fostering synergy between humans and Cyber-Physical Systems of Systems …
Intelligence, fostering synergy between humans and Cyber-Physical Systems of Systems …
[PDF][PDF] Efficient Anomaly Detection on Temporal Data via Echo State Networks and Dynamic Thresholding.
Embedded devices are frequently used to deploy adaptive learning systems for several
applications, such as anomaly detection models in automotive or aerospace domains …
applications, such as anomaly detection models in automotive or aerospace domains …