المؤلفون: Bunse, Mirko^{Aff1, IDs10618024010672_cor1}, Moreo, Alejandro, Sebastiani, Fabrizio, Senz, Martin

المصدر: Data Mining and Knowledge Discovery. :1-46

المؤلفون: González, Pablo^{Aff1, IDs10618024010141_cor1}, Moreo, Alejandro, Sebastiani, Fabrizio

المصدر: Data Mining and Knowledge Discovery. 38(4):1670-1712

المؤلفون: Moreo, Alejandro^Aff14, Sebastiani, Fabrizio^Aff14

المساهمون: Goos, Gerhard, Founding Editor^Aff1, Hartmanis, Juris, Founding Editor^Aff2, Bertino, Elisa, Editorial Board Member^Aff3, Gao, Wen, Editorial Board Member^Aff4, Steffen, Bernhard, Editorial Board Member^Aff5, Woeginger, Gerhard, Editorial Board Member^Aff6, Yung, Moti, Editorial Board Member^Aff7, Hiemstra, Djoerd, editor^Aff8, Moens, Marie-Francine, editor^Aff9, Mothe, Josiane, editor^Aff10, Perego, Raffaele, editor^Aff11, Potthast, Martin, editor^Aff12, Sebastiani, Fabrizio, editor^Aff13

المصدر: Advances in Information Retrieval : 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 – April 1, 2021, Proceedings, Part II. 12657:75-91

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المؤلفون: Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani

المصدر: The Information Retrieval Series ISBN: 9783031204661

مصطلحات موضوعية: Quantification, Learning to Quantify

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5936d6d02036c4333f40ded022492e58
https://openportal.isti.cnr.it/doc?id=people______::a9ec320dbddc78a905d0c6dfb5040d3f

المؤلفون: Bunse, Mirko, Moreo, Alejandro, Sebastiani, Fabrizio, Senz, Martin

المصدر: Machine Learning and Knowledge Discovery in Databases ISBN: 9783031264184
ECML/PKDD 2022-33rd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pp. 36–52, Grenoble, France, 19-23/09/2022

مصطلحات موضوعية: Learning to quantify

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c3b72fb7090b9f50d6f3a59eef4b684

المؤلفون: Del Coz J. J, González P., Moreo A., Sebastiani F.

مصطلحات موضوعية: Quantification, Learning to quantify

URL الوصول: https://explore.openaire.eu/search/publication?articleId=od______9984::c177cd24b4efaae1bb93c3d8050b28b4
https://openportal.isti.cnr.it/doc?id=people______::77254d513ec599c1bb6c83843eb5f4b3

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المؤلفون: Moreo, Esuli, Sebastiani

المصدر: CIKM
CIKM 2021-30th International Conference on Information and Knowledge Management, pp. 4534–4543, Online conference, 01-05/11/2021
info:cnr-pdr/source/autori:Moreo A.; Esuli A.; Sebastiani F./congresso_nome:CIKM 2021-30th International Conference on Information and Knowledge Management/congresso_luogo:Online conference/congresso_data:01-05%2F11%2F2021/anno:2021/pagina_da:4534/pagina_a:4543/intervallo_pagine:4534–4543
Proceedings of the 30th ACM International Conference on Information & Knowledge Management

مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer science, 02 engineering and technology, Machine learning, computer.software_genre, Machine Learning (cs.LG), Software, Quantification, 020204 information systems, Classifier (linguistics), 0202 electrical engineering, electronic engineering, information engineering, Learning to quantify, computer.programming_language, Class (computer programming), Computer Science - Computation and Language, business.industry, Model selection, Supervised learning, Python (programming language), Visualization, Artificial Intelligence (cs.AI), Quantifier (logic), 020201 artificial intelligence & image processing, Artificial intelligence, business, Computation and Language (cs.CL), computer

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e95006bbf35055033f3c6ade36397356
https://doi.org/10.1145/3459637.3482015

المؤلفون: Alessandro Fabris, Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani

المصدر: Journal of artificial intelligence research (Online) 76 (2023): 1117–1180. doi:10.1613/jair.1.14033

مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Machine Learning, Fairness, Artificial Intelligence, Quantification, Computers and Society (cs.CY), Learning to quantify, Machine Learning (cs.LG)

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a657f6374d3e17b8244e8aada225eec
http://arxiv.org/abs/2109.08549