News Archive
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Paper accepted at UAI - July 21, 2021
Our paper Random Probabilistic Circuits, Nicola Di Mauro, Gennaro Gala, Marco Iannotta, Teresa M.A. Basile, has been accepted for publication in UAI 2021.
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Paper accepted at IEEE Access - January 20, 2020
Our paper Multi-Channel Deep Feature Learning for Intrusion Detection, Giusseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba, has been accepted for publication in IEEE Access Journal.
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Paper accepted at Journal of Intelligent Information Systems - September 18, 2019
Our paper Ensembles of density estimators for positive-unlabeled learning, Teresa M.A. Basile, Nicola Di Mauro, Floriana Esposito, Stefano Ferilli, Antonio Vergari, has been accepted for publication in Journal of Intelligent Information Systems.
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Paper accepted at Machine Learning Journal - September 18, 2018
Our paper Visualizing and understanding Sum-Product Networks, A. Vergari, N. Di Mauro and F. Esposito, has been accepted for publication in Machine Learning Journal.
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Paper accepted at AIXIA 2018 - September 10, 2018
Our paper Extremely Randomized CNets for Multi-label Classification, T.M.A. Basile, N. Di Mauro and F. Esposito, has been accepted for publication in the proceedings of AIXIA 2018.
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Paper accepted at ISMIS 2018 - September 1, 2018
Our paper Unsupervised LSTMs-based Learning for Anomaly Detection in Highway Traffic Data, N. Di Mauro and S. Ferilli, has been accepted for publication in the proceedings of ISMIS 2018.
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Papers accepted at AAAI 2018 - November 24, 2017
Our two papers Sum-Product Autoencoding: Encoding and Decoding Representations using Sum-Product Networks, A. Vergari, R. Peharz, N. Di Mauro, A. Molina, K. Kersting, F. Esposito, and Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains, A. Molina, A. Vergari, N. Di Mauro, S. Natarajan, F. Esposito, K. Kersting, have been accepted for publication in the proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018).
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1st place at TiSeLaC ECML/PKDD 2017 challenge - July 28, 2017
Our deep learning approach learning different representations for time series land cover classification reached 1st place at TiSeLaC ECML PKDD 2017 challenge. End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification N. Di Mauro, A. Vergari, T.M.A. Basile, F.G. Ventola, F. Esposito, Proc. ECML/PKDD DC, 2017
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Paper accepted at ECML/PKDD 2017 - July 20, 2017
The paper Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks, N. Di Mauro, A. Vergari, T.M.A. Basile, F. Esposito, has been accepted for publication in the proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2017).
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Paper accepted at ICLR 2017 - April 4, 2017
The paper Encoding and Decoding Representations with Sum- and Max-Product Networks, A. Vergari, R. Peharz, N. Di Mauro, F. Esposito, has been accepted for publication in the proceedings of the 5th International Conference on Learning Representations Workshop track (ICLR 2017).
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Paper accepted at PGM 2016 - July 11, 2016
The paper Multi-Label Classification with Cutset Networks, N. Di Mauro, A. Vergari, and F. Esposito, has been accepted for publication in the proceedings of the 8th International Conference on Probabilistic Graphical Models (PGM 2016).
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Upcoming events, PGM 2016 - December 24, 2015
The International Conference on Probabilistic Graphical Models, September 6-9 2016
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Paper accepted at ISMIS 2015 - July 15, 2015
Our paper Learning Bayesian Random Cutset Forests, N. Di Mauro, A. Vergari, and T.M.A. Basile, has been accepted for publication at ISMIS 2015.
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Paper accepted at AIXIA 2015 - July 1, 2015
Our paper Learning Accurate Cutset Networks by Exploiting Decomposability, N. Di Mauro, A. Vergari, and F. Esposito, has been accepted for publication at AIXIA 2015.
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Paper accepted at ECML PKDD 2015 - June 1, 2015
Our paper Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning, A. Vergari, N. Di Mauro, and F. Esposito, has been accepted for publication at ECML PKDD 2015.
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Paper accepted at Machine Learning Journal - May 28, 2015
Our paper Bandit-Based Monte-Carlo Structure Learning of Probabilistic Logic Programs, N. Di Mauro, E. Bellodi, and F. Riguzzi, has been accepted for publication in Machine Learning Journal.