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University of Milano-Bicocca
Department of Informatics, Systems and Communication
Fabio Stella is Associate Professor in the Department of Informatics, Systems and Communication at the University of Milano-Bicocca. He received his Ph.D. in Computational Mathematics and Operations Research at University of Milano in 1995. He worked as assistant professor in University of Milano from 1993 to 1998 before joining the University of Milano-Bicocca in 1998. He worked as research assistant in the EEC IMPROD project devoted to improve quality of semiconductors using the Data Mining methodology. From 1998 to 2000 he worked as research leader in the Pirelli P-Vision project to improve tyre performance using Data Mining. From 2000 to 2001 he was consultant for the Risk Management of Banca Intesa. His main research activities include; Bayesian networks, continuous time Bayesian networks, Feedforward neural networks, on-line portfolio selection algorithms and probabilistic topic models. He serves as referee for many International Journals; Journal of Approximate Reasoning, Expert Systems with Applications, Data Mining and Knowledge Discovery, Information Processing and Management, European Journal of Operations research, and Quantitative Finance. From 2015, he is member of the Programme Committee of the Uncertaininty in Artificial Intelligence conference. He teaches Probability and Statistics for Bachelor of Science in Informatics and Data and Text Mining for Master of Science in Informatics at the University of Milano-Bicocca. He also teaches Data Mining in foreign Universities.
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Università di Milano-Bicocca
Data Mining - Clustering and Association
- 40 Ore
- 14 Set 2016
- Non impostato
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Dettagli dell'utente
FABIO STELLA
fabio.stella@unimib.it
University of Milano-Bicocca
Department of Informatics, Systems and Communication
Nazione
Italia
Città /Località
Milano
Attività di autenticazione
Primo accesso al sitolunedì, 30 novembre 2015, 13:54 (8 anni 360 giorni)
Ultimo accesso al sitolunedì, 11 gennaio 2021, 12:29 (3 anni 316 giorni)
Indirizzo IP più recente93.56.161.37