Per Year
@article{skeislr-acmcs, acm = {3645103}, articleno = 161, author = {Ciatto, Giovanni and Sabbatini, Federico and Agiollo, Andrea and Magnini, Matteo and Omicini, Andrea}, doi = {10.1145/3645103}, eissn = {1557-734}, iris = {11585/969235}, issn = {0360-0300}, journal = {ACM Computing Surveys}, keywords = {Logic; Machine learning theory; Hybrid symbolic-numeric methods; Knowledge representation and reasoning}, month = jun, number = 6, numpages = 35, pages = {161:1--161:35}, publisher = {ACM}, scholar = {13701373869146776438}, scopus = {2-s2.0-85188835517}, semanticscholar = {267611660}, title = {Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review}, url = {https://dl.acm.org/doi/10.1145/3645103}, urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3645103}, urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3645103}, volume = 56, wos = {WOS:001208566200027}, year = 2024 }
@article{ndnfl-fgcs2023, author = {Agiollo, Andrea and Enkeleda Bardhi and Mauro Conti and Nicolò Dal Fabbro and Riccardo Lazzeretti}, doi = {10.1016/j.future.2023.11.009}, issn = {0167-739X}, journal = {Future Generation Computer Systems}, keywords = {Anonymous communication, Federated Learning, Named Data Networking, Privacy-preserving}, pages = {288--303}, publisher = {Elsevier}, note = {Special Issue on Federated Learning on the Edge: Challenges and Future Directions}, title = {Anonymous Federated Learning via Named-Data Networking}, url = {https://www.sciencedirect.com/science/article/pii/S0167739X23004144}, volume = 152, year = 2024 }
@article{eneafl-fgcs154, author = {Agiollo, Andrea and Bellavista, Paolo and Mendula, Matteo and Omicini, Andrea}, doi = {10.1016/j.future.2024.01.007}, editor = {Hao Wu and Carlo Puliafito and Omer F. Rana and Luiz F. Bittencourt}, iris = {11585/953081}, issn = {0167-739X}, journal = {Future Generation Computer Systems}, keywords = {Serverless, Federated Learning, Energy Management, Internet of Things, Resource-constrained Learning}, month = may, note = {Special Issue ``Serverless Computing in the Cloud-to-Edge Continuum''}, numpages = 16, pages = {219--234}, publisher = {Elsevier Science B.V.}, scholar = {15164122000920541506}, scopus = {2-s2.0-85182399653}, title = {{EneA-FL}: Energy-aware Orchestration for Serverless Federated Learning}, url = {https://www.sciencedirect.com/science/article/pii/S0167739X24000074}, volume = 154, wos = {WOS:001164533000001}, year = 2024 }
@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 }