Denis Deratani MauŠ
Denis Deratani MauŠ
Professor, Dept. of Computer Science, Institute of Mathematics and Statistics, Universidade de S„o
Verified email at usp.br - Homepage
Title
Cited by
Cited by
Year
An Ensemble of Bayesian Networks for Multilabel Classification
A Alessandro, G Corani, D MauŠ, S Gabaglio
Twenty-Third International Joint Conference on Artificial Intelligence, 1220†…, 2013
51*2013
Evaluating credal classifiers by utility-discounted predictive accuracy
M Zaffalon, G Corani, D MauŠ
International Journal of Approximate Reasoning 53 (8), 1282-1301, 2012
482012
Solving limited memory influence diagrams
DD MauŠ, CP de Campos, M Zaffalon
Journal of Artificial Intelligence Research 44, 97-140, 2012
302012
Probabilistic inference in credal networks: new complexity results
DD MauŠ, CP De Campos, A Benavoli, A Antonucci
Journal of Artificial Intelligence Research 50, 603-637, 2014
292014
Advances in learning Bayesian networks of bounded treewidth
S Nie, DD MauŠ, CP De Campos, Q Ji
Advances in neural information processing systems, 2285-2293, 2014
292014
Anytime Marginal MAP Inference
C Campos, DD Maua
29th International Conference on Machine Learning (ICML-12), 1471-1478, 2012
27*2012
Approximation complexity of maximum a posteriori inference in sum-product networks
D Conaty, DD MauŠ, CP De Campos
arXiv preprint arXiv:1703.06045, 2017
222017
On the Complexity of Strong and Epistemic Credal Networks
DD MauŠ, CP de Campos, A Benavoli, A Antonucci
29th Conference on Uncertainty in Artificial Intelligence (UAI-13), 391-400, 2013
182013
Equivalences between maximum a posteriori inference in bayesian networks and maximum expected utility computation in influence diagrams
DD MauŠ
International Journal of Approximate Reasoning 68, 211-229, 2016
172016
Trading off speed and accuracy in multilabel classification
G Corani, A Antonucci, DD MauŠ, S Gabaglio
European Workshop on Probabilistic Graphical Models, 145-159, 2014
172014
Updating credal networks is approximable in polynomial time
DD MauŠ, CP De Campos, M Zaffalon
International Journal of Approximate Reasoning 53 (8), 1183-1199, 2012
162012
Solving decision problems with limited information
DD MauŠ, C Campos
Advances in Neural Information Processing Systems (NIPS-11), 603-611, 2011
162011
Utility-based accuracy measures to empirically evaluate credal classifiers
M Zaffalon, G Corani, D MauŠ
Seventh International Symposium on Imprecise Probability: Theories and†…, 2011
152011
Credal sum-product networks
DD MauŠ, FG Cozman, D Conaty, CP Campos
Proceedings of the Tenth International Symposium on Imprecise Probability†…, 2017
142017
Bayesian Networks Specified Using Propositional and Relational Constructs: Combined, Data, and Domain Complexity
FG Cozman, DD Maua
Twenty-Ninth AAAI Conference on Artificial Intelligence, 3519-3525, 2015
142015
On the semantics and complexity of probabilistic logic programs
FG Cozman, DD MauŠ
Journal of Artificial Intelligence Research 60, 221-262, 2017
132017
Robustifying sum-product networks
DD MauŠ, D Conaty, FG Cozman, K Poppenhaeger, CP de Campos
International Journal of Approximate Reasoning 101, 163-180, 2018
122018
The Complexity of Approximately Solving Influence Diagrams
DD MauŠ, CP de Campos, M Zaffalon
Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI-12†…, 2012
122012
Hidden Markov models with set-valued parameters
DD Maua, A Antonucci, CP de Campos
Neurocomputing 180, 94-107, 2016
112016
The complexity of MAP inference in Bayesian networks specified through logical languages
DD MauŠ, CP De Campos, FG Cozman
International Joint Conference on Artificial Intelligence 24, 889-895, 2015
102015
The system can't perform the operation now. Try again later.
Articles 1–20