Artikel dengan mandat akses publik - Marco ZaffalonPelajari lebih lanjut
Tersedia di suatu tempat: 79
Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis
A Benavoli, G Corani, J Demšar, M Zaffalon
Journal of Machine Learning Research 18 (77), 1-36, 2017
Mandat: Swiss National Science Foundation
Learning Bayesian networks with thousands of variables
M Scanagatta, CP de Campos, G Corani, M Zaffalon
Advances in neural information processing systems 28, 2015
Mandat: Swiss National Science Foundation
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process
A Benavoli, G Corani, F Mangili, M Zaffalon, F Ruggeri
International conference on machine learning, 1026-1034, 2014
Mandat: Swiss National Science Foundation
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2.
G Corani, M Zaffalon
Journal of Machine Learning Research 9 (4), 2008
Mandat: Swiss National Science Foundation
Evaluating credal classifiers by utility-discounted predictive accuracy
M Zaffalon, G Corani, D Mauá
International Journal of Approximate Reasoning 53 (8), 1282-1301, 2012
Mandat: Swiss National Science Foundation
Independent natural extension
G De Cooman, E Miranda, M Zaffalon
Artificial Intelligence 175 (12-13), 1911-1950, 2011
Mandat: Swiss National Science Foundation, Research Foundation (Flanders)
Epistemic irrelevance in credal nets: the case of imprecise Markov trees
G De Cooman, F Hermans, A Antonucci, M Zaffalon
International Journal of Approximate Reasoning 51 (9), 1029-1052, 2010
Mandat: Swiss National Science Foundation, Research Foundation (Flanders)
Statistical comparison of classifiers through Bayesian hierarchical modelling
G Corani, A Benavoli, J Demšar, F Mangili, M Zaffalon
Machine Learning 106, 1817-1837, 2017
Mandat: Swiss National Science Foundation
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, 2016
Mandat: Swiss National Science Foundation
Bayesian networks with imprecise probabilities: Theory and application to classification
G Corani, A Antonucci, M Zaffalon
Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering …, 2012
Mandat: Swiss National Science Foundation
Conservative inference rule for uncertain reasoning under incompleteness
M Zaffalon, E Miranda
Journal of Artificial Intelligence Research 34, 757-821, 2009
Mandat: Swiss National Science Foundation
Entropy-based pruning for learning Bayesian networks using BIC
CP de Campos, M Scanagatta, G Corani, M Zaffalon
Artificial Intelligence 260, 42-50, 2018
Mandat: Swiss National Science Foundation
Decision-theoretic specification of credal networks: a unified language for uncertain modeling with sets of Bayesian networks
A Antonucci, M Zaffalon
International Journal of Approximate Reasoning 49 (2), 345-361, 2008
Mandat: Swiss National Science Foundation
Time series forecasting with gaussian processes needs priors
G Corani, A Benavoli, M Zaffalon
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
Mandat: Swiss National Science Foundation
Approximate structure learning for large Bayesian networks
M Scanagatta, G Corani, CP De Campos, M Zaffalon
Machine Learning 107, 1209-1227, 2018
Mandat: Swiss National Science Foundation
Solving limited memory influence diagrams
DD Mauá, CP de Campos, M Zaffalon
Journal of Artificial Intelligence Research 44, 97-140, 2012
Mandat: Swiss National Science Foundation
Inference and risk measurement with the pari-mutuel model
R Pelessoni, P Vicig, M Zaffalon
International Journal of Approximate Reasoning 51 (9), 1145-1158, 2010
Mandat: Swiss National Science Foundation
Probability and time
M Zaffalon, E Miranda
Artificial Intelligence 198, 1-51, 2013
Mandat: Swiss National Science Foundation
Robust filtering through coherent lower previsions
A Benavoli, M Zaffalon, E Miranda
IEEE Transactions on Automatic Control 56 (7), 1567-1581, 2010
Mandat: Swiss National Science Foundation
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
Mandat: Swiss National Science Foundation
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