Andrea Agiollo

Orcid: 0000-0003-0531-1978

According to our database1, Andrea Agiollo authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review.
ACM Comput. Surv., June, 2024

Anonymous Federated Learning via Named-Data Networking.
Future Gener. Comput. Syst., March, 2024

2023
Symbolic knowledge injection meets intelligent agents: QoS metrics and experiments.
Auton. Agents Multi Agent Syst., October, 2023

Peer-Reviewed Federated Learning.
Proceedings of the 24th Workshop "From Objects to Agents", 2023

Measuring Trustworthiness in Neuro-Symbolic Integration.
Proceedings of the 18th Conference on Computer Science and Intelligence Systems, 2023

The Quarrel of Local Post-hoc Explainers for Moral Values Classification in Natural Language Processing.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2023

GNN4IFA: Interest Flooding Attack Detection With Graph Neural Networks.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

DETONAR-Light: An IoT Network Intrusion Detection Using DETONAR without a Sniffer Network.
Proceedings of the Computer Security. ESORICS 2023 International Workshops, 2023

2022
Towards quality-of-service metrics for symbolic knowledge injection.
Proceedings of the 23rd Workshop "From Objects to Agents", 2022

GNN2GNN: Graph neural networks to generate neural networks.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
DETONAR: Detection of Routing Attacks in RPL-Based IoT.
IEEE Trans. Netw. Serv. Manag., 2021

Graph Neural Networks as the Copula Mundi between Logic and Machine Learning: a Roadmap.
Proceedings of the 22nd Workshop "From Objects to Agents", 2021

Shallow2Deep: Restraining Neural Networks Opacity Through Neural Architecture Search.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2021

2019
Region Merging Driven by Deep Learning for RGB-D Segmentation and Labeling.
Proceedings of the 13th International Conference on Distributed Smart Cameras, 2019


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