Mauro Scanagatta
Mauro Scanagatta
Researcher, FBK - DAS
Email verificata su fbk.eu - Home page
Titolo
Citata da
Citata da
Anno
Learning Bayesian networks with thousands of variables
M Scanagatta, CP de Campos, G Corani, M Zaffalon
Advances in neural information processing systems 28, 1864-1872, 2015
672015
Air pollution prediction via multi-label classification
G Corani, M Scanagatta
Environmental modelling & software 80, 259-264, 2016
382016
Learning treewidth-bounded Bayesian networks with thousands of variables
M Scanagatta, G Corani, CP De Campos, M Zaffalon
Advances in neural information processing systems 29, 1462-1470, 2016
272016
Approximate structure learning for large Bayesian networks
M Scanagatta, G Corani, CP De Campos, M Zaffalon
Machine Learning 107 (8-10), 1209-1227, 2018
202018
A survey on Bayesian network structure learning from data
M Scanagatta, A Salmerón, F Stella
Progress in Artificial Intelligence, 1-15, 2019
192019
Learning extended tree augmented naive structures
CP de Campos, G Corani, M Scanagatta, M Cuccu, M Zaffalon
International Journal of Approximate Reasoning 68, 153-163, 2016
172016
Entropy-based pruning for learning Bayesian networks using BIC
CP de Campos, M Scanagatta, G Corani, M Zaffalon
Artificial Intelligence 260, 42-50, 2018
112018
Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets
M Scanagatta, G Corani, M Zaffalon, J Yoo, U Kang
International Journal of Approximate Reasoning 95, 152-166, 2018
112018
Min-BDeu and max-BDeu scores for learning Bayesian networks
M Scanagatta, CP De Campos, M Zaffalon
European Workshop on Probabilistic Graphical Models, 426-441, 2014
92014
Improved local search in Bayesian networks structure learning
M Scanagatta, G Corani, M Zaffalon
Advanced Methodologies for Bayesian Networks, 45-56, 2017
82017
Early classification of time series by hidden markov models with set-valued parameters
A Antonucci, M Scanagatta, DD Mauá, CP de Campos
Proceedings of the NIPS Time Series Workshop, 2015
52015
Advancements in Bayesian network structure learning
M Scanagatta
Università della Svizzera Italiana, 2018
12018
Learning Bounded Treewidth Bayesian Networks with Thousands of Variables
M Scanagatta, G Corani, CP de Campos, M Zaffalon
arXiv preprint arXiv:1605.03392, 2016
12016
Calibration of game dynamics for a more even multi-player experience
M Scanagatta, M Ferron, G Deppieri, A Marconi
Proceedings of the 25th International Conference on Intelligent User …, 2020
2020
Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference
J Yoo, U Kang, M Scanagatta, G Corani, M Zaffalon
Proceedings of the 13th International Conference on Web Search and Data …, 2020
2020
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–15