2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Opportunistic Information-Bottleneck for Goal-oriented Feature Extraction and Communication
Francesco Binucci, Paolo Banelli, Paolo Di Lorenzo +1
The Information Bottleneck (IB) method is an information theoretical framework to design a parsimonious and tunable feature-extraction mechanism, such that the extracted features a…
Enabling Edge Artificial Intelligence via Goal-oriented Deep Neural Network Splitting
Francesco Binucci, Mattia Merluzzi, Paolo Banelli +2
Deep Neural Network (DNN) splitting is one of the key enablers of edge Artificial Intelligence (AI), as it allows end users to pre-process data and offload part of the computationa…
Goal-oriented Communications for the IoT: System Design and Adaptive Resource Optimization
Paolo Di Lorenzo, Mattia Merluzzi, Francesco Binucci +4
Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and pr…
Multi-user Goal-oriented Communications with Energy-efficient Edge Resource Management
Francesco Binucci, Paolo Banelli, Paolo Di Lorenzo +1
Edge Learning (EL) pushes the computational resources toward the edge of 5G/6G network to assist mobile users requesting delay-sensitive and energy-aware intelligent services. A co…