Per Year

@incollection{shallow2deep-extraamas2021,
   address = {Cham, Switzerland},
   author = {Agiollo, Andrea and Ciatto, Giovanni and Omicini, Andrea},
   booktitle = {Explainable and Transparent AI and Multi-Agent Systems. Third International Workshop, EXTRAAMAS 2021, Virtual Event, May 3--7, 2021, Revised Selected Papers},
   dblp = {conf/atal/AgiolloCO21},
   doi = {10.1007/978-3-030-82017-6_5},
   editor = {Calvaresi, Davide and Najjar, Amro and Winikoff, Michael and Fr{\"a}mling, Kary},
   eisbn = {978-3-030-82017-6},
   eissn = {1611-3349},
   iris = {11585/838540},
   isbn = {978-3-030-82016-9},
   issn = {0302-9743},
   keywords = {Neural Architecture Search; Evolutionary Algorithm; Opacity; Interpretability},
   numpages = 20,
   pages = {63--82},
   publisher = {Springer},
   scholar = {8606811357246615623},
   scopus = {2-s2.0-85113325735},
   semanticscholar = {236460263},
   series = {Lecture Notes in Computer Science},
   subseries = {Lecture Notes in Artificial Intelligence},
   title = {{\it Shallow2Deep}: Restraining Neural Networks Opacity through Neural Architecture Search},
   url = {http://link.springer.com/10.1007/978-3-030-82017-6_5},
   volume = 12688,
   wos = {000691781800005},
   year = 2021
}

@article{nnconstrained-applsci11,
   articleno = 11957,
   author = {Agiollo, Andrea and Omicini, Andrea},
   doi = {10.3390/app112411957},
   iris = {11585/842440},
   issn = {2076-3417},
   journal = {Applied Sciences},
   keywords = {Load Classification; Neural Networks; Embedding; Hyper-constrained Devices},
   month = dec,
   note = {Special Issue ``Artificial Intelligence and Data Engineering in Engineering Applications''},
   number = 24,
   publisher = {MDPI},
   scholar = {14515352047550375229},
   scopus = {2-s2.0-85121296114},
   title = {Load Classification: A Case Study for Applying Neural Networks in Hyper-Constrained Embedded Devices},
   url = {https://www.mdpi.com/2076-3417/11/24/11957},
   url-openaccess = {https://www.mdpi.com/2076-3417/11/24/11957/pdf},
   urlopenaccess = {https://www.mdpi.com/2076-3417/11/24/11957/pdf},
   urlpdf = {https://www.mdpi.com/2076-3417/11/24/11957/pdf},
   volume = 11,
   wos = {000735509300001},
   year = 2021
}

@article{detonar-ieetnsm2021,
   author = {Agiollo, Andrea and Conti, Mauro and Kaliyar, Pallavi and Lin, TsungNan and Pajola, Luca},
   doi = {10.1109/TNSM.2021.3075496},
   ieee = {9415869},
   iris = {11585/842654},
   issn = {1932-4537},
   journal = {IEEE Transactions on Network and Service Management},
   keywords = {Internet of Things, Low Power and Lossy Networks, Routing Protocol, Networking attacks, Intrusion Detection System},
   number = 2,
   numpages = 13,
   pages = {1178 - 1190},
   publisher = {IEEE},
   title = {{DETONAR}: Detection of Routing Attacks in {RPL}-based {I}o{T}},
   url = {https://ieeexplore.ieee.org/document/9415869},
   urlpdf = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9415869},
   volume = 18,
   wos = {000660636700006},
   year = 2021
}

@inproceedings{gnn-woa2021,
   articleno = 8,
   author = {Agiollo, Andrea and Ciatto, Giovanni and Omicini, Andrea},
   booktitle = {WOA 2021 -- 22nd Workshop ``From Objects to Agents''},
   dblp = {conf/woa/AgiolloCO21},
   editor = {Calegari, Roberta and Ciatto, Giovanni and Denti, Enrico and Omicini, Andrea and Sartor, Giovanni},
   iris = {11585/834362},
   issn = {1613-0073},
   keywords = {Graph Neural Networks, Machine Learning, Embedding, Computational Logic},
   location = {Bologna, Italy},
   month = oct,
   note = {22nd Workshop ``From Objects to Agents'' (WOA 2021), Bologna, Italy, 1--3~} # sep # {~2021. Proceedings},
   numpages = 18,
   pages = {98--115},
   publisher = {Sun SITE Central Europe, RWTH Aachen University},
   scholar = {817372786663443317},
   scopus = {2-s2.0-85116916925},
   semanticscholar = {238360605},
   series = {CEUR Workshop Proceedings},
   subseries = {AI*IA Series},
   title = {Graph Neural Networks as the Copula Mundi between Logic and Machine Learning: A Roadmap},
   url = {http://ceur-ws.org/Vol-2963/paper18.pdf},
   volume = 2963,
   year = 2021
}