Publications (4)
A cumulative approach to quantification for sentiment analysis
Giambattista Amati, Simone Angelini, Marco Bianchi +2
We estimate sentiment categories proportions for retrieval within large retrieval sets. In general, estimates are produced by counting the classification outcomes and then by adjus…
AI-Driven Multi-Hop Relay Selection for Smart Urban NR-V2X Networks via Learning-to-Optimize Graph Neural Networks
Giambattista Amati, Federica Mangiatordi, Simone Angelini +2
Reliable and low-latency NR-V2X communications are essential for smart mobility in dense urban environments. However, limited Road-Side Unit (RSU) density, frequent non-line-of-sig…
Low-Latency Relay Selection in NR-V2X Vehicular Communications via Graph Isomorphism Networks with Edge Features
Giambattista Amati, Federica Mangiatordi, Emiliano Pallotti +3
The paper proposes a graph‑neural‑network approach (GINE) to select relay nodes for low‑latency NR‑V2X communications, using edge features and an offline MILP oracle to train the m…
PROPAGATE: a seed propagation framework to compute Distance-based metrics on Very Large Graphs
Giambattista Amati, Antonio Cruciani, Daniele Pasquini +2
We propose PROPAGATE, a fast approximation framework to estimate distance-based metrics on very large graphs such as the (effective) diameter, the (effective) radius, or the averag…