Per Year
- Anonymous Federated Learning via Named-Data Networking (article in journal) — Andrea Agiollo, Enkeleda Bardhi, Mauro Conti, Nicolò Dal Fabbro, Riccardo Lazzeretti
- EneA-FL: Energy-aware Orchestration for Serverless Federated Learning (article in journal) — Andrea Agiollo, Paolo Bellavista, Matteo Mendula, Andrea Omicini
- GNN4IFA: Interest Flooding Attack Detection With Graph Neural Networks (paper in proceedings) — Andrea Agiollo, Enkeleda Bardhi, Mauro Conti, Riccardo Lazzeretti, Eleonora Losiouk, Andrea Omicini
- Measuring Trustworthiness in Neuro-Symbolic Integration (paper in proceedings) — Andrea Agiollo, Andrea Omicini
- Peer-Reviewed Federated Learning (paper in proceedings) — Mattia Passeri, Andrea Agiollo, Andrea Omicini
- The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing (paper in proceedings) — Andrea Agiollo, Luciano C. Siebert, Pradeep K. Murukannaiah, Andrea Omicini
- Symbolic Knowledge Injection meets Intelligent Agents: QoS metrics and experiments (article in journal) — Andrea Agiollo, Andrea Rafanelli, Matteo Magnini, Giovanni Ciatto, Andrea Omicini
- Towards Quality-of-Service Metrics for Symbolic Knowledge Injection (paper in proceedings) — Andrea Agiollo, Andrea Rafanelli, Andrea Omicini
- GNN2GNN: Graph Neural Networks to Generate Neural Networks (paper in proceedings) — Andrea Agiollo, Andrea Omicini
- Shallow2Deep: Restraining Neural Networks Opacity through Neural Architecture Search (paper in proceedings) — Andrea Agiollo, Giovanni Ciatto, Andrea Omicini
- Load Classification: A Case Study for Applying Neural Networks in Hyper-Constrained Embedded Devices (article in journal) — Andrea Agiollo, Andrea Omicini
- DETONAR: Detection of Routing Attacks in RPL-based IoT (article in journal) — Andrea Agiollo, Mauro Conti, Pallavi Kaliyar, TsungNan Lin, Luca Pajola
- Graph Neural Networks as the Copula Mundi between Logic and Machine Learning: A Roadmap (paper in proceedings) — Andrea Agiollo, Giovanni Ciatto, Andrea Omicini
- Region Merging Driven by Deep Learning for RGB-D Segmentation and Labeling (paper in proceedings) — Umberto Michieli, Maria Camporese, Andrea Agiollo, Giampaolo Pagnutti, Pietro Zanuttigh
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