E-LIB Suche - Ergebnisse für: Scanagatta, Mauro

1

A Gamification Platform to Analyze and Influence Citizens' ..:

Kazhamiakin, Raman ; Loria, Enrica ; Marconi, Annapaola.
IEEE Transactions on Intelligent Transportation Systems. 22 (2021) 4 - p. 2153-2167 , 2021

Link: https://doi.org/10.1109/..

2

Calibration of game dynamics for a more even multi-player e..:

, In: Proceedings of the 25th International Conference on Intelligent User Interfaces,

Scanagatta, Mauro ; Ferron, Michela ; Deppieri, Giulia. - p. 443-453 , 2020

Link: https://dl.acm.org/doi/1..

3

Sampling Subgraphs with Guaranteed Treewidth for Accurate a..:

, In: Proceedings of the 13th International Conference on Web Search and Data Mining,

Yoo, Jaemin ; Kang, U ; Scanagatta, Mauro.. - p. 708-716 , 2020

Link: https://dl.acm.org/doi/1..

4

A survey on Bayesian network structure learning from data:

Scanagatta, Mauro ; Salmerón, Antonio ; Stella, Fabio
Progress in Artificial Intelligence. 8 (2019) 4 - p. 425-439 , 2019

Link: https://doi.org/10.1007/..

5

Approximate structure learning for large Bayesian networks:

Scanagatta, Mauro ; Corani, Giorgio ; de Campos, Cassio Polpo.
Machine Learning. 107 (2018) 8-10 - p. 1209-1227 , 2018

Link: https://doi.org/10.1007/..

6

Entropy-based pruning for learning Bayesian networks using ..:

de Campos, Cassio P. ; Scanagatta, Mauro ; Corani, Giorgio.
Artificial Intelligence. 260 (2018) - p. 42-50 , 2018

Link: https://doi.org/10.1016/..

7

Efficient learning of bounded-treewidth Bayesian networks f..:

Scanagatta, Mauro ; Corani, Giorgio ; Zaffalon, Marco..
International Journal of Approximate Reasoning. 95 (2018) - p. 152-166 , 2018

Link: https://doi.org/10.1016/..

8

Air pollution prediction via multi-label classification:

Corani, Giorgio ; Scanagatta, Mauro
Environmental Modelling & Software. 80 (2016) - p. 259-264 , 2016

Link: https://doi.org/10.1016/..

9

Learning extended tree augmented naive structures:

de Campos, Cassio P. ; Corani, Giorgio ; Scanagatta, Mauro..
International Journal of Approximate Reasoning. 68 (2016) - p. 153-163 , 2016

Link: https://doi.org/10.1016/..

10

How to Design Personalized Challenges for Mobile Motivation..:

, In: Lecture Notes in Computer Science; Games and Learning Alliance,

Mauro, Scanagatta ; Annapaola, Marconi - p. 245-251 , 2021

Link: https://doi.org/10.1007/..

11

A survey on Bayesian network structure learning from data:

Scanagatta, Mauro ; Salmerón, Antonio ; Stella, Fabio
info:eu-repo/semantics/altIdentifier/wos/WOS:000493607900002. , 2019

Link: http://hdl.handle.net/10..

12

Efficient Learning of Bounded-Treewidth Bayesian Networks f..:

Scanagatta, Mauro ; Corani, Giorgio ; Zaffalon, Marco..
http://arxiv.org/abs/1802.02468. , 2018

Link: http://arxiv.org/abs/180..

13

Entropy-based Pruning for Learning Bayesian Networks using ..:

de Campos, Cassio ; Scanagatta, Mauro ; Corani, Giorgio.
https://dspace.library.uu.nl/handle/1874/364435. , 2018

Link: https://dspace.library.u..

14

Entropy-based Pruning for Learning Bayesian Networks using ..:

de Campos, Cassio P ; Scanagatta, Mauro ; Corani, Giorgio.
http://arxiv.org/abs/1707.06194. , 2017

Link: http://arxiv.org/abs/170..

15

Learning Extended Tree Augmented Naive Structures:

de Campos, Cassio P ; Corani, Giorgio ; Scanagatta, Mauro..
de Campos , C P , Corani , G , Scanagatta , M , Cuccu , M & Zaffalon , M 2016 , ' Learning Extended Tree Augmented Naive Structures ' , International Journal of Approximate Reasoning , vol. 68 , pp. 153-163 . https://doi.org/10.1016/j.ijar.2015.04.006. , 2016

Link: https://pure.qub.ac.uk/e..