Publications

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2020

 Perplexity-free Parametric t-SNE

Crecchi, Francesco; de Bodt, Cyril; Bacciu, Davide; Verleysen, Michel; John, Lee

Perplexity-free Parametric t-SNE Conference

Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN'20), 2020.

BibTeX | Tags: data visualization, manifold learning, neural networks, unsupervised learning

2019

Reti neurali e linguaggio. Le insidie nascoste di un'algebra delle parole

Bacciu, Davide

Reti neurali e linguaggio. Le insidie nascoste di un'algebra delle parole Online

Tavosanis, Mirko (Ed.): Lingua Italiana - Treccani 2019.

Links | BibTeX | Tags: artificial intelligence, natural language processing, neural networks

2018

Text Summarization as Tree Transduction by Top-Down TreeLSTM

Davide, Bacciu; Antonio, Bruno

Text Summarization as Tree Transduction by Top-Down TreeLSTM Conference

Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (SSCI'18), IEEE, 2018.

Abstract | Links | BibTeX | Tags: deep learning, deep learning for graphs, neural networks, structured data processing, tree structured data, tree transductions

Marco, Podda; Davide, Bacciu; Alessio, Micheli; Roberto, Bellu; Giulia, Placidi; Luigi, Gagliardi

A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor Journal Article

In: Nature Scientific Reports, vol. 8, 2018.

Abstract | Links | BibTeX | Tags: bioinformatics, biomedical data, neural networks, support vector machine

2011

H, Jarman Ian; A, Etchells Terence; Davide, Bacciu; M, Garibaldi John; O, Ellis Ian; JG, Lisboa Paulo

Clustering of protein expression data: a benchmark of statistical and neural approaches Journal Article

In: Soft Computing-A Fusion of Foundations, Methodologies and Applications, vol. 15, no. 8, pp. 1459–1469, 2011, ISSN: 1432-7643.

Links | BibTeX | Tags: biomedical data, clustering, neural networks, statistics, unsupervised learning

2010

S, Fernandes Ana; Davide, Bacciu; H, Jarman Ian; A, Etchells Terence; M, Fonseca Jose; JG, Lisboa Paulo

Different Methodologies for Patient Stratification Using Survival Data Conference

Lecture Notes in Computer ScienceComputational Intelligence Methods for Bioinformatics and Biostatistics, vol. 6160, 2010.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, neural networks, statistics, survival analysis, unsupervised learning

2009

Davide, Bacciu; Antonina, Starita

Expansive competitive learning for kernel vector quantization Journal Article

In: Pattern Recognition Letters, vol. 30, no. 6, pp. 641–651, 2009, ISSN: 0167-8655.

Links | BibTeX | Tags: clustering, competitive repetition suppression learning, kernel methods, neural networks, statistics, unsupervised learning

JG, Lisboa Paulo; H, Jarman Ian; A, Etchells Terence; Davide, Bacciu; M, Garibaldi John

Model-based and model-free clustering: a case study of protein expression data for breast cancer Conference

PROCEEDINGS OF THE 2009 UK WORKSHOP ON COMPUTATIONAL INTELLIGENCE, 2009.

BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, feature selection, neural networks, unsupervised learning

S, Fernandes Ana; Davide, Bacciu; H, Jarman Ian; A, Etchells Terence; M, Fonseca Jose; Lisboa, Paulo J G

p-Health in Breast Oncology: A Framework for Predictive and Participatory e-Systems Conference

2009 Second International Conference on Developments in eSystems Engineering, IEEE, 2009.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, neural networks

Davide, Bacciu; H, Jarman Ian; A, Etchells Terence; G, Lisboa Paulo J

Patient stratification with competing risks by multivariate Fisher distance Conference

2009 International Joint Conference on Neural Networks, IEEE, 2009.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, generative model, neural networks, statistics, survival analysis, unsupervised learning

2008

Davide, Bacciu; Antonina, Starita

Competitive Repetition Suppression (CoRe) Clustering: A Biologically Inspired Learning Model With Application to Robust Clustering Journal Article

In: Neural Networks, IEEE Transactions on, vol. 19, no. 11, pp. 1922 -1941, 2008, ISSN: 1045-9227.

Links | BibTeX | Tags: biologically inspired learning, clustering, competitive repetition suppression learning, neural networks, soft competitive learning, unsupervised learning

Davide, Bacciu

A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections PhD Thesis

2008.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, feature selection, generative model, graphical models, image understanding, latent topic model, neural networks, statistics, unsupervised learning

Davide, BACCIU; Elia, BIGANZOLI; JG, LISBOA Paulo; Antonina, Starita

Are Model-based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics Conference

Proceedings of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES'08), vol. 5178, Springer, 2008.

Abstract | Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, feature selection, neural networks, statistics, unsupervised learning

Davide, Bacciu; Antonina, Starita

Convergence Behavior of Competitive Repetition-Suppression Clustering Conference

Neural Information Processing, Lecture Notes in Computer Science, vol. 4984, Springer, 2008.

Abstract | Links | BibTeX | Tags: clustering, competitive repetition suppression learning, neural networks, statistics, unsupervised learning

2007

Davide, Bacciu; Alessio, Micheli; Antonina, Starita

Feature-wise Competitive Repetition Suppression Learning for Gene Data Clustering and Feature Ranking Technical Report

Università di Pisa 2007.

Links | BibTeX | Tags: biomedical data, clustering, competitive repetition suppression learning, feature selection, kernel methods, neural networks