Publications

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2020

Bacciu, Davide; Errica, Federico; Micheli, Alessio

Probabilistic Learning on Graphs via Contextual Architectures Journal Article

In: Journal of Machine Learning Research, vol. 21, no. 134, pp. 1−39, 2020.

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

2019

A non-negative factorization approach to node pooling in graph convolutional neural networks

Bacciu, Davide; Sotto, Luigi Di

A non-negative factorization approach to node pooling in graph convolutional neural networks Conference

Proceedings of the 18th International Conference of the Italian Association for Artificial Intelligence (AIIA 2019), Lecture Notes in Artificial Intelligence Springer-Verlag, 2019.

Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

Castellana, Daniele; Bacciu, Davide

Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models Conference

Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN 2019I) , IEEE, 2019.

Abstract | Links | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data; tensor factorization; Bayesian learning

Bayesian Mixtures of Hidden Tree Markov Models for Structured Data Clustering

Davide, Bacciu; Daniele, Castellana

Bayesian Mixtures of Hidden Tree Markov Models for Structured Data Clustering Journal Article

In: Neurocomputing, vol. 342, pp. 49-59, 2019, ISBN: 0925-2312.

Abstract | Links | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data, unsupervised learning

2018

Davide, Bacciu; Daniele, Castellana

Learning Tree Distributions by Hidden Markov Models Workshop

Proceedings of the FLOC 2018 Workshop on Learning and Automata (LearnAut'18), 2018.

Links | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data

Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing

Davide, Bacciu; Federico, Errica; Alessio, Micheli

Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing Conference

Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 2018.

Links | BibTeX | Tags: deep learning, deep learning for graphs, graph data, hidden tree Markov model, structured data processing

Davide, Bacciu; Daniele, Castellana

Mixture of Hidden Markov Models as Tree Encoder Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'18), i6doc.com, Louvain-la-Neuve, Belgium, 2018, ISBN: 978-287587047-6.

Abstract | BibTeX | Tags: graphical models, hidden tree Markov model, structured data processing, tree structured data, unsupervised learning

Generative Kernels for Tree-Structured Data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Generative Kernels for Tree-Structured Data Journal Article

In: Neural Networks and Learning Systems, IEEE Transactions on, 2018, ISSN: 2162-2388 .

Abstract | Links | BibTeX | Tags: hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data

2017

Davide, Bacciu

Hidden Tree Markov Networks: Deep and Wide Learning for Structured Data Conference

Proc. of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI'17), IEEE, 2017.

Links | BibTeX | Tags: deep learning, hidden tree Markov model, structured data processing

2014

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Integrating bi-directional contexts in a generative kernel for trees Conference

Neural Networks (IJCNN), 2014 International Joint Conference on, IEEE, 2014.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data, tree transductions

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Modeling Bi-directional Tree Contexts by Generative Transductions Conference

Neural Information Processing, vol. 8834, Springer International Publishing, 2014.

Abstract | Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, tree kernel, tree structured data

2013

Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model Journal Article

In: Neural Networks and Learning Systems, IEEE Transactions on, vol. 24, no. 2, pp. 231 -247, 2013, ISSN: 2162-237X.

Links | BibTeX | Tags: generative topographic mapping, hidden Markov models, hidden tree Markov model, self-organizing map, tree structured data

An input–output hidden Markov model for tree transductions

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

An input–output hidden Markov model for tree transductions Journal Article

In: Neurocomputing, vol. 112, pp. 34–46, 2013, ISSN: 0925-2312.

Links | BibTeX | Tags: hidden Markov models, hidden tree Markov model, structured data processing, tree transductions

2012

Compositional Generative Mapping for Tree-Structured Data; Part I: Bottom-Up Probabilistic Modeling of Trees

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Compositional Generative Mapping for Tree-Structured Data; Part I: Bottom-Up Probabilistic Modeling of Trees Journal Article

In: Neural Networks and Learning Systems, IEEE Transactions on, vol. 23, no. 12, pp. 1987 -2002, 2012, ISSN: 2162-237X.

Links | BibTeX | Tags: hidden Markov models, hidden tree Markov model, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

A Generative Multiset Kernel for Structured Data Conference

Artificial Neural Networks and Machine Learning - ICANN 2012 proceedings, Springer LNCS series, vol. 7552, Springer-Verlag, BERLIN HEIDELBERG, 2012.

Abstract | Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, kernel methods, structured data processing, support vector machine, tree kernel, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Input-Output Hidden Markov Models for Trees Conference

ESANN 2012 - The 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings, Ciaco scrl - i6doc.com, 2012.

Abstract | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data, tree transductions

2011

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Adaptive Tree Kernel by Multinomial Generative Topographic Mapping Conference

Proceedings of the International Joint Conference on Neural Networks, IEEE, Piscataway (NJ), 2011.

Links | BibTeX | Tags: generative model, generative topographic mapping, graphical models, hidden tree Markov model, kernel methods, structured data processing, tree kernel, tree structured data

2010

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

A Bottom-up Hidden Tree Markov Model Technical Report

Università di Pisa no. TR-10-08, 2010.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Bottom-Up Generative Modeling of Tree-Structured Data Conference

LNCS 6443: Neural Information Processing. Theory and Algorithms. Part I, vol. 6443, Springer-Verlag, BERLIN HEIDELBERG, 2010.

Links | BibTeX | Tags: generative model, graphical models, hidden tree Markov model, structured data processing, tree structured data

Davide, Bacciu; Alessio, Micheli; Alessandro, Sperduti

Compositional Generative Mapping of Structured Data Conference

Proceedings of the 2010 IEEE InternationalJoint Conference on Neural Networks(IJCNN'10), IEEE, 2010.

Links | BibTeX | Tags: generative topographic mapping, graphical models, hidden tree Markov model, structured data processing, tree structured data, unsupervised learning