Per anno

 @article{skeislr-csur56,
    acm = {3645103},
    articleno = 161,
    author = {Ciatto, Giovanni and Sabbatini, Federico and Agiollo, Andrea and Magnini, Matteo and Omicini, Andrea},
    dblp = {journals/csur/CiattoSAMO24},
    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{skenlp-jaamas38,
    articleno = 32,
    author = {Agiollo, Andrea and Siebert, Luciano Cavalcante and Murukannaiah, Pradeep Kumar and Omicini, Andrea},
    dblp = {journals/aamas/AgiolloSMO24},
    doi = {10.1007/s10458-024-09663-8},
    iris = {11585/973894},
    journal = {Autonomous Agents and Multi-Agent Systems},
    keywords = {Natural language processing, post-hoc explanations, symbolic knowledge extraction, eXplainable AI, resource-friendly AI},
    month = jul,
    note = {Special Issue on Multi-Agent Systems and Explainable AI},
    numpages = 33,
    pages = {1--33},
    publisher = {Springer},
    scholar = {13114388339509722903},
    scopus = {2-s2.0-85197706028},
    title = {From Large Language Models to Small Logic Programs: Building Global Explanations from Disagreeing Local Post-hoc Explainers},
    url = {http://link.springer.com/10.1007/s10458-024-09663-8},
    urlopenaccess = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
    urlpdf = {https://link.springer.com/content/pdf/10.1007/s10458-024-09663-8.pdf},
    volume = 38,
    wos = {WOS:001264787900001},
    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},
    dblp = {journals/fgcs/AgiolloBMO24},
    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
} 

 @inproceedings{skidatadegradation-woa2024,
    author = {Rafanelli, Andrea and Magnini, Matteo and Agiollo, Andrea and Ciatto, Giovanni and Omicini, Andrea},
    booktitle = {WOA 2024 -- 25th Workshop ``From Objects to Agents 2024''},
    dblp = {conf/woa/RafanelliMACO24},
    editor = {Alderighi, Marco and Baldoni, Matteo and Baroglio, Cristina and Micalizio, Roberto and Tedeschi, Stefano},
    iris = {11585/975934},
    issn = {1613-0073},
    keywords = {Symbolic Knowledge Injection, Robustness, Neural Networks},
    location = {Bard, AO, Italy},
    month = jul,
    numpages = 13,
    pages = {20--32},
    publisher = {Sun SITE Central Europe, RWTH Aachen University},
    scopus = {2-s2.0-85200118300},
    series = {CEUR Workshop Proceedings},
    subseries = {AIxIA Series},
    title = {An Empirical Study on the Robustness of Knowledge Injection Techniques Against Data Degradation},
    url = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    urlopenaccess = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    urlpdf = {https://ceur-ws.org/Vol-3735/paper_02.pdf},
    volume = 3735,
    year = 2024
} 

 @inproceedings{samis-kdd2024,
    acm = {3671985},
    author = {Agiollo, Andrea and Young In Kim and Khanna, Rajiv},
    dblp = {conf/kdd/AgiolloKK24},
    doi = {10.1145/3637528.3671985},
    journal = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24), August 25–29, 2024, Barcelona, Spain},
    keywords = {Neural Networks, Data-efficient Learning, Memorization, Flatness},
    month = aug,
    numpages = 12,
    pages = {17--28},
    publisher = {ACM},
    scholar = {8151925308990231563},
    title = {Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization},
    url = {https://dl.acm.org/doi/10.1145/3637528.3671985},
    urlopenaccess = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
    urlpdf = {https://dl.acm.org/doi/pdf/10.1145/3637528.3671985},
    year = 2024
}