3. Diego Sona

Diego Sona

Affiliated Researcher

Research Lines

Center

Contacts

Via Enrico Melen 83, Edificio B, 16152, Genova, Italy
+39 010 2897 424

About

Diego Sona is a researcher at the Fondazione Bruno Kessler (FBK) in the Neuroinformatics Laboratory (NILab) and visiting scientist at the Istituto Italiano di Tecnologia (IIT) leading the Biomedical Imaging team in the Pattern Analysis and Computer Vision (PAVIS) department.

He received the Ph.D degree in Computer Science in 2002 from the University of Pisa with a thesis on modeling  of artificial neural networks through formal methods. From 2002 to 2008 he served as researcher in the Adaptive Advisory Systems Group at the Istituto Trentino di Cultura, investigating machine learning models for structured data and contextual processing, with main application to information retrieval and text data management. In 2008 he moved to the Neuroinformatics Laboratory at FBK, studying multivariate pattern analysis methods for brain decoding and brain mapping from functional brain imaging.  In 2010 he became tenured researcher at FBK. From 2008 to 2011 he has been guest researcher at the Center for Mind/Brain Sciences in the University of Trento. Since 2011 he joined as a visiting scientist the Pattern Analysis and Computer Vision department at the Istituto Italiano di Tecnologia leading the activities in biomedical imaging.

His research is on machine learning and pattern recognition methods, with application to various domains, like information retrieval, structured data analysis, computer vision, neuroimaging and biomedical imaging. The most significant recent research activity spans various automatic methods for animal phenotyping, ranging from video and signal analysis for social and non-social behavior understanding, to the investigation of corresponding neuronal correlates: from functional and structural brain imaging down to the analysis of meso-scale neuronal network populations.

He has co-authored more than 70 peer-reviewed publications, published in refereed journals and international conferences and served as reviewer for several international journals and conferences.

 

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Projects

My main research interest has always been on machine learning and its application to real problems. Since some years now I am interested on the design of novel solutions allowing to investigate the multiple facets of behavioral phenotyping. This allows to explore many aspects of neuroscience and biology domains: from the phenotyping of social and non-social behaviors to the investigation of corresponding brain correlates, from the characterization of cells and neuronal network connectivity to the analysis of the manifestations of certain mental diseases (such as schizophrenia, autism, etc.), through structural and functional brain imaging. In this perspective, the research on biomedical data analysis currently carried out by my team can be seen as organized around three main research lines:

Funded Projects

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IIT Publications

  • 2021
  • Doria S., Valeri F., Lasagni L., Sanguineti V.iit, Ragonesi R.iit, Akbar M.U.iit, Gnerucci A., Del Bue A.iit, Marconi A., Risaliti G., Grigioni M., Miele V., Sona D.iit, Cisbani E., Gori C., Taddeucci A.
    DOI

    Addressing signal alterations induced in CT images by deep learning processing: A preliminary phantom study

    Physica Medica, vol. 83, pp. 88-100
  • Soda P., D'Amico N.C., Tessadori J.iit, Valbusa G., Guarrasi V., Bortolotto C., Akbar M.U.iit, Sicilia R., Cordelli E., Fazzini D., Cellina M., Oliva G., Callea G., Panella S., Cariati M., Cozzi D., Miele V., Stellato E., Carrafiello G., Castorani G., Simeone A., Preda L., Iannello G., Del Bue A.iit, Tedoldi F., Ali M., Sona D.iit, Papa S.
    DOI

    AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study

    Medical Image Analysis, vol. 74
  • Tessadori J.iit, Yamin M.A.iit, Valsasina P., Filippi M., Rocca M.A., Sona D.iit
    DOI

    Dynamic functional connectivity for the classification of multiple sclerosis phenotype: A hidden markov model approach

    Proceedings - International Symposium on Biomedical Imaging, vol. 2021-April, pp. 559-562
  • Iandolo R.iit, Semprini M.iit, Sona D.iit, Mantini D., Avanzino L., Chiappalone M.iit
    DOI

    Investigating the spectral features of the brain meso-scale structure at rest

    Human Brain Mapping, vol. 42, (no. 15), pp. 5113-5129
  • Akbar M.U.iit, Murino V.iit, Sona D.iit
    DOI

    Multimodal segmentation of medical images with heavily missing data

    BHI 2021 - 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, Proceedings
  • Akbar M.U.iit, Murino V., Sona D.iit
    DOI

    Multimodal Segmentation of Medical Images with Heavily Missing Data

    IEEE EMBS International Conference on Biomedical and Health Informatics
  • Akbar M.U.iit, Yamin M.A.iit, Murino V.iit, Sona D.iit
    DOI

    Organ Segmentation with Recursive Data Augmentation for Deep Models

    Lecture Notes in Computer Science, vol. 12661 LNCS, pp. 337-343
  • Crimi A.iit, Dodero L.iit, Sambataro F., Murino V.iit, Sona D.iit
    DOI

    Structurally constrained effective brain connectivity

    NeuroImage, vol. 239
  • 2020
  • Astolfi P.iit, De Benedictis A., Sarubbo S., Berto G., Olivetti E., Sona D.iit, Avesani P.
    DOI

    A Stem-Based Dissection of Inferior Fronto-Occipital Fasciculus with A Deep Learning Model

    Proceedings - International Symposium on Biomedical Imaging, vol. 2020-April, pp. 267-270
  • Astolfi P.iit, De Benedictis A., Sarubbo S., Berto G., Olivetti E., Sona D.iit, Avesani P.
    DOI

    A STEM-BASED DISSECTION OF INFERIOR FRONTO-OCCIPITAL FASCICULUS WITH A DEEP LEARNING MODEL

    IEEE International Symposium on Biomedical Imaging
  • Yamin M.A.iit, Valsasina P., Dayan M., Vascon S., Tessadori J.iit, Filippi M., Murino V.iit, Rocca M.A., Sona D.iit
    DOI

    Encoding brain networks through geodesic clustering of functional connectivity for multiple sclerosis classification

    Proceedings - International Conference on Pattern Recognition, pp. 10106-10112
  • Yamin A.iit, Paola V., Dayan M., Vascon S., Tessadori J.iit, Massimo F., Murino V.iit, Maria A.R., Sona D.iit

    Encoding Brain Networks Through Geodesic Clustering of Functional Connectivity for Multiple Sclerosis Classification

    25th International Conference on Pattern Recognition
  • Yamin M.A.iit, Tessadori J.iit, Akbar M.U.iit, Dayan M., Murino V.iit, Sona D.iit
    DOI

    Geodesic Clustering of Positive Definite Matrices for Classification of Mental Disorder Using Brain Functional Connectivity

    Proceedings of the International Joint Conference on Neural Networks
  • Volpi R., Zanotto M.iit, Maccione A.iit, Di Marco S., Berdondini L.iit, Sona D.iit, Murino V.iit
    DOI

    Modeling a population of retinal ganglion cells with restricted Boltzmann machines

    Scientific Reports, vol. 10, (no. 1)
  • Aslani S.iit, Murino V.iit, Dayan M., Tam R., Sona D.iit, Hamarneh G.
    DOI

    Scanner Invariant Multiple Sclerosis Lesion Segmentation from MRI

    Proceedings - International Symposium on Biomedical Imaging, vol. 2020-April, pp. 781-785
  • Hati A., Bustreo M., Sona D., Murino V., Del Bue A.iit
    DOI

    Weakly supervised geodesic segmentation of Egyptian mummy CT scans

    Proceedings - International Conference on Pattern Recognition, pp. 5565-5572
  • 2019
  • Yamin A.iit, Dayan M.iit, Squarcina L., Brambilla P., Murino V.iit, Diwadkar V., Sona D.iit
    DOI

    Analysis of dynamic brain connectivity through geodesic clustering

    Lecture Notes in Computer Science, vol. 11752 LNCS, pp. 640-648
  • Yamin A.iit, Dayan M.iit, Squarcina L., Brambilla P., Murino V.iit, Diwadkar V., Sona D.iit
    DOI

    Comparison of brain connectomes using geodesic distance on manifold: A twins study

    Proceedings - International Symposium on Biomedical Imaging, vol. 2019-April, pp. 1797-1800
  • Aslani S.iit, Dayan M.iit, Murino V.iit, Sona D.iit
    DOI

    Deep 2D encoder-decoder convolutional neural network for multiple sclerosis lesion segmentation in brain MRI

    Lecture Notes in Computer Science, vol. 11383 LNCS, pp. 132-141
  • Yamin M.A.iit, Dayan M.iit, Squarcina L., Diwadkar V., Brambilla P., Murino V.iit, Sona D.iit
    DOI

    Investigating the impact of genetic background on brain dynamic functional connectivity through machine learning: A twins study

    2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings
  • Aslani S.iit, Dayan M.iit, Storelli L., Filippi M., Murino V.iit, Rocca M.A., Sona D.iit
    DOI

    Multi-branch convolutional neural network for multiple sclerosis lesion segmentation

    NeuroImage, vol. 196, pp. 1-15
  • Crimi A.iit, Giancardo L.iit, Sambataro F., Gozzi A.iit, Murino V.iit, Sona D.iit
    DOI

    MultiLink Analysis: Brain Network Comparison via Sparse Connectivity Analysis

    Scientific Reports, vol. 9, (no. 1)
  • Akbar M.U.iit, Aslani S.iit, Murino V.iit, Sona D.iit
    DOI

    Multiple organs segmentation in abdomen CT scans using a cascade of CNNs

    Lecture Notes in Computer Science, vol. 11751 LNCS, pp. 509-516
  • Akbar M.U.iit, Murino V.iit, Sona D.iit
    DOI

    Segmentation of Kidney and Tumor using Auxiliary Information

    University of Minnesota Digital Conservancy
  • 2018
  • Katsageorgiou V.-M.iit, Sona D.iit, Zanotto M.iit, Lassi G.iit, Garcia-Garcia C.iit, Tucci V.iit, Murino V.iit
    DOI

    A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice

    PLoS Biology, vol. 16, (no. 5)
  • Baglietto S.iit, Kepiro I.E.iit, Hilgen G., Sernagor E., Murino V.iit, Sona D.iit
    DOI

    Automatic segmentation of neurons from fluorescent microscopy imaging

    Communications in Computer and Information Science, vol. 881, pp. 121-133
  • Sadafi A.iit, Katsageorgiou V.-M.iit, Huang H.iit, Papaleo F.iit, Murino V.iit, Sona D.iit
    DOI

    Multiple Mice Tracking: Occlusions Disentanglement using a Gaussian Mixture Model

    Proceedings - International Conference on Pattern Recognition, vol. 2018-August, pp. 2433-2437
  • Dayan M.iit, Katsageorgiou V.-M.iit, Dodero L.iit, Murino V.iit, Sona D.iit
    DOI

    Unsupervised Detection of White Matter Fiber Bundles with Stochastic Neural Networks

    Proceedings - International Conference on Image Processing, ICIP, pp. 3513-3517
  • 2017
  • Baglietto S.iit, Dayan M.iit, Murino V.iit, Sona D.iit

    3D dendrite tracing inspired by diffusion MRI tractography

    BioImage Informatics Conference
  • Gomez C.H.iit, Dodero L.iit, Gozzi A.iit, Murino V.iit, Sona D.iit
    DOI

    Atlas-free connectivity analysis driven by white matter structure

    Proceedings - International Symposium on Biomedical Imaging, pp. 89-92
  • Crimi A.iit, Dodero L.iit, Murino V.iit, Sona D.iit
    DOI

    Case-control discrimination through effective brain connectivity

    Proceedings - International Symposium on Biomedical Imaging, pp. 970-973
  • Katsageorgiou V.-M.iit, Zanotto M.iit, Tucci V.iit, Murino V.iit, Sona D.iit
    DOI

    Data-driven study of mouse sleep-stages using Restricted Boltzmann Machines

    Proceedings of the International Joint Conference on Neural Networks, vol. 2017-May, pp. 4549-4556
  • Crimi A., Dodero L., Sambataro F., Murino V.iit, Sona D.iit

    Effective Brain Connectivity based on Structural Prior

    annual meeting of the organization for human brain mapping
  • Baglietto S.iit, Kepiro I.E.iit, Hilgen G., Sernagor E., Murino V.iit, Sona D.iit
    DOI

    Segmentation of retinal ganglion cells from fluorescent microscopy imaging

    BIOIMAGING 2017 - 4th International Conference on Bioimaging, Proceedings; Part of 10th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2017, vol. 2017-January, pp. 17-23
  • Dayan M.iit, Rocca M., Valsasina P., Pagani E., Murino V.iit, Filippi M., Sona D.iit

    Sparse representation of the connectome for group discrimination: application to multiple sclerosis

    annual meeting of the organization for human brain mapping
  • Hilgen G., Sorbaro M., Pirmoradian S., Muthmann J.-O., Kepiro I.E.iit, Ullo S.iit, Ramirez C.J., Puente Encinas A., Maccione A.iit, Berdondini L.iit, Murino V.iit, Sona D.iit, Cella Zanacchi F.iit, Sernagor E., Hennig M.H.
    DOI

    Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

    Cell Reports, vol. 18, (no. 10), pp. 2521-2532
  • 2016
  • Crimi A.iit, Dodero L.iit, Murino V.iit, Sona D.iit
    DOI

    Effective brain connectivity through a constrained autoregressive model

    Lecture Notes in Computer Science, vol. 9900 LNCS, pp. 140-147
  • Sadafi A., Katsageorgiou V.-M.iit, Huang H., Papaleo F.iit, Murino V.iit, Sona D.iit

    Multiple Mice Tracking and Segmentation through SIFT Flow Analysis

    23rd International Conference on Pattern Recognition, ICPR 2016, Cancún, Mexico, December 4-8, 2016, (no. Visual Observation and Analysis of Vertebrate And Insect Behavior Workshop)
  • Dodero L.iit, Sona D.iit, Meskaldji D.E., Murino V.iit, Van De Ville D.
    DOI

    Traces of human functional activity: Moment-to-moment fluctuations in fMRI data

    Proceedings - International Symposium on Biomedical Imaging, vol. 2016-June, pp. 1307-1310
  • Katsageorgiou V.-M.iit, Zanotto M.iit, Huang H.iit, Ferretti V.iit, Papaleo F.iit, Sona D.iit, Murino V.iit
    DOI

    Unsupervised mouse behavior analysis: A data-driven study of mice interactions

    Proceedings - International Conference on Pattern Recognition, vol. 0, pp. 925-930
  • 2015
  • Dodero L.iit, Vascon S.iit, Murino V.iit, Bifone A.iit, Gozzi A.iit, Sona D.iit
    DOI

    Automated multi-subject fiber clustering of mouse brain using dominant sets

    Frontiers in Neuroinformatics, vol. 8, (no. JAN)
  • Ullo S.iit, Murino V.iit, Maccione A.iit, Berdondini L.iit, Sona D.iit
    DOI

    Bridging the gap in connectomic studies: A particle filtering framework for estimating structural connectivity at network scale

    Medical Image Analysis, vol. 21, (no. 1), pp. 1-14
  • Gomez C.H.iit, Medathati K., Kornprobst P., Murino V.iit, Sona D.iit
    DOI

    Improving freak descriptor for image classification

    Lecture Notes in Computer Science, vol. 9163, pp. 14-23
  • Dodero L.iit, Sambataro F., Murino V.iit, Sona D.iit
    DOI

    Kernel-based analysis of functional brain connectivity on Grassmann manifold

    Lecture Notes in Computer Science, vol. 9351, pp. 604-611
  • Dodero L.iit, Minh H.Q.iit, Biagio M.S.iit, Murino V.iit, Sona D.iit
    DOI

    Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices

    Proceedings - International Symposium on Biomedical Imaging, vol. 2015-July, pp. 42-45
  • Zanotto M.iit, Di Marco S.iit, Maccione A.iit, Berdondini L.iit, Sona D.iit, Murino V.iit

    Modelling Retinal Activity with Restricted Boltzmann Machines: a Study on the Inhibitory Circuitry

    Computational and Systems Neuroscience 2015
  • Murino V.iit, Puppo E., Sona D.iit, Cristani M., Sansone C.

    New trends in image analysis and processing – ICIAP 2015 workshops: ICIAP 2015 international workshops BioFor, CTMR, RHEUMA, ISCA, MADiMa SBMI, and QoEM Genoa, Italy, september 7–8, 2015 proceedings

    Lecture Notes in Computer Science, vol. 9281
  • Avesani P., Hazan H., Koilis E., Manevitz L.M., Sona D.iit
    DOI

    Non-parametric temporal modeling of the hemodynamic response function via a liquid state machine

    Neural Networks, vol. 70, pp. 61-73
  • Murino V.iit, Puppo E., Sona D.iit, Cristani M., Sansone C.

    Preface

    Lecture Notes in Computer Science, vol. 9281, pp. V-VIII
  • Katsageorgiou V.-M.iit, Lassi G.iit, Tucci V.iit, Murino V.iit, Sona D.iit
    DOI

    Sleep-stage scoring in mice: The influence of data pre-processing on a system's performance

    Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, vol. 2015-November, pp. 598-601
  • 2014
  • Huang H.iit, Michetti C., Busnelli M., Manago F.iit, Sannino S.iit, Scheggia D.iit, Giancardo L.iit, Sona D.iit, Murino V.iit, Chini B., Scattoni M.L., Papaleo F.iit
    DOI

    Chronic and acute intranasal oxytocin produce divergent social effects in mice

    Neuropsychopharmacology, vol. 39, (no. 5), pp. 1102-1114
  • Pisani P.iit, Piro P.iit, Decherchi S.iit, Bottegoni G.iit, Sona D.iit, Murino V.iit, Rocchia W.iit, Cavalli A.iit
    DOI

    Describing the conformational landscape of small organic molecules through Gaussian mixtures in dihedral space

    Journal of Chemical Theory and Computation, vol. 10, (no. 6), pp. 2557-2568
  • Ullo S.iit, Nieus T.R.iit, Sona D.iit, Maccione A.iit, Berdondini L.iit, Murino V.iit
    DOI

    Functional connectivity estimation over large networks at cellular resolution based on electrophysiological recordings and structural prior

    Frontiers in Neuroanatomy, vol. 8, (no. NOV)
  • Dodero L.iit, Gozzi A.iit, Liska A.iit, Murino V.iit, Sona D.iit
    DOI

    Group-wise functional community detection through joint Laplacian diagonalization

    Lecture Notes in Computer Science, vol. 8674 LNCS, (no. PART 2), pp. 708-715
  • Dodero L.iit, Murino V.iit, Sona D.iit
    DOI

    Joint laplacian diagonalization for multi-modal brain community detection

    Proceedings - 2014 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2014
  • 2013
  • Giancardo L.iit, Sona D.iit, Huang H.iit, Sannino S.iit, Manago F.iit, Scheggia D.iit, Papaleo F.iit, Murino V.iit
    DOI

    Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice

    PLoS ONE, vol. 8, (no. 9)
  • Dodero L., Vascon S., Giancardo L., Gozzi A.iit, Sona D.iit, Murino V.iit
    DOI

    Automatic White Matter Fiber Clustering Using Dominant Sets

    Proceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
  • Zanotto M.iit, Sona D.iit, Murino V.iit, Papaleo F.iit
    DOI

    Dirichlet process mixtures of multinomials for data mining in mice behaviour analysis

    Proceedings of the IEEE International Conference on Computer Vision, pp. 197-202
  • Ullo S.iit, Castellani U., Sona D.iit, Del Bue A.iit, Maccione A.iit, Berdondini L.iit, Murino V.iit
    DOI

    Neuronal network structural connectivity estimation by probabilistic features and graph heat kernels

    Proceedings - International Symposium on Biomedical Imaging, pp. 1054-1057
  • Ullo S.iit, Castellani U., Sona D.iit, Del Bue A.iit, Maccione A.iit, Berdondini L.iit, Murino V.iit

    Neuronal Network Structural Connectivity Estimation by Probabilistic Features and Graph Heat Kernels

    IEEE 10th International Symposium on Biomedical Imaging, pp. 1054-1057
  • 2012
  • Giancardo L.iit, Sona D.iit, Gozzi A.iit, Bifone A.iit, Murino V.iit, Migliarini S., Pacini G., Pelosi B., Pasqualetti M.
    DOI

    Automatic tractography analysis through sparse networks in case-control studies

    Proceedings - 2012 2nd International Workshop on Pattern Recognition in NeuroImaging, PRNI 2012, pp. 77-80
  • Bjornsdotter M., Sona D.iit, Rosenthal S., Dauwels J.

    Clustered subsampling for clinically informed diagnostic brain mapping

    15th International Conference on Information Fusion, FUSION 2012, pp. 593-599
  • Piro P.iit, Pisani P.iit, Bottegoni G.iit, Sona D.iit, Rocchia W.iit, Cavalli A.iit, Murino V.iit

    Fitting and simplification of mixtures for clustering conformational populations of small organic molecules

    International Conference on Chemical and Biological Engineering
  • Piro P.iit, Sona D.iit, Murino V.iit

    Inner product tree for improved Orthogonal Matching Pursuit

    Proceedings - International Conference on Pattern Recognition, pp. 429-432
  • Sona D.iit, Avesani P., Magon S., Basso G., Miceli G.
    DOI

    Pairwise analysis for longitudinal fMRI studies

    Lecture Notes in Computer Science, vol. 7263 LNAI, pp. 132-139
  • Giancardo L.iit, Sona D.iit, Scheggia D.iit, Papaleo F.iit, Murino V.iit

    Segmentation and tracking of multiple interacting mice by temperature and shape information

    Proceedings - International Conference on Pattern Recognition, pp. 2520-2523
  • Maccione A.iit, Ullo S.iit, Simi A.iit, Nieus T.iit, Sona D.iit, Del Bue A.iit, Murino V.iit, Berdondini L.iit

    Structural and functional identification of sub-networks in dissociated neuronal cultures: an automated multimodal analysis combining high density MEA and fluorescence imaging

    8th International Meeting on Substrate-Integrated Microelectrode Arrays
  • 2011
  • Avesani P., Hazann H., Koilis E., Manevitz L., Sona D.
    DOI

    Learning BOLD response in fMRI by reservoir computing

    Proceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011, pp. 57-60
  • 2010
  • Sona D., Avesani P.
    DOI

    Feature rating by random subspaces for functional brain mapping

    Lecture Notes in Computer Science, vol. 6334 LNAI, pp. 112-123
  • Sona D., Avesani P.
    DOI

    Multivariate brain mapping by random subspaces

    Proceedings - International Conference on Pattern Recognition, pp. 2576-2579
  • 2009
  • Sona D., Olivetti E., Avesani P., Veeramachaneni S.
    DOI

    Learning to Interpret Cognitive States from fMRI Brain Images

    Frontiers in Artificial Intelligence and Applications, vol. 196, (no. 1), pp. 21-35
  • 2008
  • Polettini N., Sona D., Avesani P.
    DOI

    A relational cascade correlation for structured outputs

    Proceedings of the International Joint Conference on Neural Networks, pp. 2799-2805
  • 2007
  • Guizzardi R.S.S., Ludermir P.G., Sona D.
    DOI

    A recommender agent to support knowledge sharing in virtual enterprises

    Agent and Web Service Technologies in Virtual Enterprises, pp. 115-134, Publisher: IGI Global
  • Triolo E., Polettini N., Sona D., Avesani P.
    DOI

    Building quality-based views of the web

    Lecture Notes in Computer Science, vol. 4733 LNAI, pp. 519-530
  • Sona D., Veeramachaneni S., Olivetti E., Avesani P.
    DOI

    Inferring cognition from fMRI brain images

    Lecture Notes in Computer Science, vol. 4669 LNCS, (no. PART 2), pp. 869-878
  • 2006
  • Saini P.S., Ronchetti M., Sona D.

    Automatic generation of metadata for learning objects

    Proceedings - Sixth International Conference on Advanced Learning Technologies, ICALT 2006, vol. 2006, pp. 275-279
  • Sona D., Veeramachaneni S., Polettini N., Avesani P.
    DOI

    Regularization for unsupervised classification on taxonomies

    Lecture Notes in Computer Science, vol. 4203 LNAI, pp. 691-696
  • 2005
  • Adami G., Avesani P., Sona D.
    DOI

    Clustering documents into a web directory for bootstrapping a supervised classification

    Data and Knowledge Engineering, vol. 54, (no. 3), pp. 301-325
  • Sona D., Avesani P., Moskovitch R.
    DOI

    Helping physicians to organize guidelines within conceptual hierarchies

    Lecture Notes in Computer Science, vol. 3581 LNAI, pp. 141-145
  • Veeramachaneni S., Sona D., Avesani P.

    Hierarchical Dirichlet model for document classification

    ICML 2005 - Proceedings of the 22nd International Conference on Machine Learning, pp. 929-936
  • 2004
  • Micheli A., Sona D., Sperduti A.
    DOI

    Contextual processing of structured data by recursive cascade correlation

    IEEE Transactions on Neural Networks, vol. 15, (no. 6), pp. 1396-1410
  • 2003
  • Adami G., Avesani P., Sona D.
    DOI

    Bootstrapping for hierarchical document classification

    International Conference on Information and Knowledge Management, Proceedings, pp. 295-302
  • Adami G., Avesani P., Sona D.
    DOI

    Clustering documents in a web directory

    Proceedings of the Interntational Workshop on Web Information and Data Management, pp. 66-73
  • Micheli A., Sona D., Sperduti A.
    DOI

    Formal determination of context in contextual recursive cascade correlation networks

    Lecture Notes in Computer Science, vol. 2714, pp. 173-180
  • 2002
  • Micheli A., Sona D., Sperduti A.

    Recursive cascade correlation for contextual processing of structured data

    Proceedings of the International Joint Conference on Neural Networks, vol. 1, pp. 268-273
  • 2001
  • Borger E., Sona D.

    A neural abstract machine

    Journal of Universal Computer Science, vol. 7, (no. 11), pp. 1006-1023
  • 2000
  • Micheli A., Sona D., Sperduti A.
    DOI

    Bi-causal recurrent cascade correlation

    Proceedings of the International Joint Conference on Neural Networks, vol. 3, pp. 3-8
  • Sona D., Sperduti A., Starita A.
    DOI

    Discriminant pattern recognition using transformation-invariant neurons

    Neural Computation, vol. 12, (no. 6), pp. 1355-1370
  • 1997
  • Sona D., Sperduti A., Starits A.

    A constructive learning algorithm for discriminant tangent models

    Advances in Neural Information Processing Systems, pp. 786-791