Francesco BUSOLIN

Position
PhD Student
Dottorato
INFORMATICA
37° Ciclo - Immatricolati nel 2021
Area tematica
Improve Learning To Rank systems with accessory models
Supervisore
Orlando Salvatore / Lucchese Claudio
E-mail
francesco.busolin@unive.it
851884@stud.unive.it
Website
www.unive.it/people/francesco.busolin (personal record)
Office
Department of Environmental Sciences, Informatics and Statistics
Website: https://www.unive.it/dep.dais

Publications

Year Type Publication
Year Type Publication
2024 Article in Conference Proceedings Francesco Busolin;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando;Raffaele Perego;Salvatore Trani Early Exit Strategies for Approximate k-NN Search in Dense Retrieval in Francesco Busolin; Claudio Lucchese; Franco Maria Nardini; Salvatore Orlando; Raffaele Perego; Salvatore Trani, CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, New York, Association for Computing Machinery, pp. 3647-3652, Convegno: CIKM '24: The 33rd ACM International Conference on Information and Knowledge Management, 21/10/2024-25/10/2024 (ISBN 979-8-4007-0436-9)
DOI - URL correlato - ARCA card: 10278/5081787
2023 Journal Article Busolin, Francesco; Lucchese, Claudio; Nardini, Franco Maria; Orlando, Salvatore; Perego, Raffaele; Trani, Salvatore Early Exit Strategies for Learning-to-Rank Cascades in IEEE ACCESS, vol. Online (ISSN 2169-3536)
DOI - ARCA card: 10278/5043380
2021 Article in Conference Proceedings Busolin F.; Lucchese C.; Nardini F.M.; Orlando S.; Perego R.; Trani S. Learning Early Exit Strategies for Additive Ranking Ensembles , SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, Inc, pp. 2217-2221, Convegno: 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021, 2021 (ISBN 9781450380379)
DOI - ARCA card: 10278/3743016