Giorgio Valentini

Giorgio Valentini, Walter Lassonde, Samee Ullah Khan, Nasro Min-Allah, Sajjad Ahmad Madani, Juan Li, Limin Zhang, Lizhe Wang, Nasir Ghani, Joanna Kolodziej, Hongxiang Li, Albert Y. Zomaya, Cheng-Zhong Xu, Pavan Balaji, Abhinav Vishnu, Frédéric Pinel, Johnatan E. Pecero, Dzmitry Kliazovich, Pascal Bouvry: An overview of energy efficiency techniques in cluster computing systems. Cluster Computing 16(1): 3-15 (2013)

Marco Frasca, Alberto Bertoni, Matteo Re, Giorgio Valentini: A neural network algorithm for semi-supervised node label learning from unbalanced data. Neural Networks 43: 84-98 (2013)

Matteo Re, Giorgio Valentini: Cancer module genes ranking using kernelized score functions. BMC Bioinformatics 13(S-14): S3 (2012)

Nicolò Cesa-Bianchi, Matteo Re, Giorgio Valentini: Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference. Machine Learning 88(1-2): 209-241 (2012)

Matteo Re, Marco Mesiti, Giorgio Valentini: A Fast Ranking Algorithm for Predicting Gene Functions in Biomolecular Networks. IEEE/ACM Trans. Comput. Biology Bioinform. 9(6): 1812-1818 (2012)

Patricia Ruiz, Bernabé Dorronsoro, Giorgio Valentini, Frédéric Pinel, Pascal Bouvry: Optimisation of the enhanced distance based broadcasting protocol for MANETs. The Journal of Supercomputing 62(3): 1213-1240 (2012)

Matteo Re, Giorgio Valentini: Random Walking on Functional Interaction Networks to Rank Genes Involved in Cancer. AIAI (2) 2012: 66-75

Matteo Re, Giorgio Valentini: Large Scale Ranking and Repositioning of Drugs with Respect to DrugBank Therapeutic Categories. ISBRA 2012: 225-236

Oleg Okun, Giorgio Valentini, Matteo Ré (Eds.): Ensembles in Machine Learning Applications. Studies in Computational Intelligence 373, Springer 2011, isbn 978-3-642-22909-1

Giorgio Valentini: True Path Rule Hierarchical Ensembles for Genome-Wide Gene Function Prediction. IEEE/ACM Trans. Comput. Biology Bioinform. 8(3): 832-847 (2011)

Marco Muselli, Alberto Bertoni, Marco Frasca, Alessandro Beghini, Francesca Ruffino, Giorgio Valentini: A Mathematical Model for the Validation of Gene Selection Methods. IEEE/ACM Trans. Comput. Biology Bioinform. 8(5): 1385-1392 (2011)

Alberto Bertoni, Marco Frasca, Giorgio Valentini: COSNet: A Cost Sensitive Neural Network for Semi-supervised Learning in Graphs. ECML/PKDD (1) 2011: 219-234

Alberto Bertoni, Matteo Re, Francesco Saccà, Giorgio Valentini: Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering. WIRN 2011: 162-169

Alessandro Rozza, Gabriele Lombardi, Matteo Re, Elena Casiraghi, Giorgio Valentini, Paola Campadelli: A Novel Ensemble Technique for Protein Subcellular Location Prediction. Ensembles in Machine Learning Applications 2011: 151-167

Matteo Re, Giorgio Valentini: Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machines. Neurocomputing 73(7-9): 1533-1537 (2010)

Matteo Re, Giorgio Valentini: Noise tolerance of Multiple Classifier Systems in data integration-based gene function prediction. J. Integrative Bioinformatics 7(3) (2010)

Nicolò Cesa-Bianchi, Giorgio Valentini: Hierarchical Cost-Sensitive Algorithms for Genome-Wide Gene Function Prediction. Journal of Machine Learning Research - Proceedings Track 8: 14-29 (2010)

Matteo Ré, Giorgio Valentini: Simple ensemble methods are competitive with state-of-the-art data integration methods for gene function prediction. Journal of Machine Learning Research - Proceedings Track 8: 98-111 (2010)

Matteo Re, Giorgio Valentini: An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction. MCS 2010: 294-303

Alberto Bertoni, Marco Frasca, Giuliano Grossi, Giorgio Valentini: Learning functional linkage networks with a cost-sensitive approach. WIRN 2010: 52-61

Oleg Okun, Giorgio Valentini (Eds.): Applications of Supervised and Unsupervised Ensemble Methods. Studies in Computational Intelligence 245, Springer 2009, isbn 978-3-642-03998-0

Giorgio Valentini, Roberto Tagliaferri, Francesco Masulli: Computational intelligence and machine learning in bioinformatics. Artificial Intelligence in Medicine 45(2-3): 91-96 (2009)

Roberto Avogadri, Giorgio Valentini: Fuzzy ensemble clustering based on random projections for DNA microarray data analysis. Artificial Intelligence in Medicine 45(2-3): 173-183 (2009)

Marco Mesiti, Ernesto Jiménez-Ruiz, Ismael Sanz, Rafael Berlanga Llavori, Paolo Perlasca, Giorgio Valentini, David Manset: XML-based approaches for the integration of heterogeneous bio-molecular data. BMC Bioinformatics 10(S-12): 7 (2009)

Roberto Avogadri, Matteo Brioschi, Fulvia Ferrazzi, Matteo Re, Alessandro Beghini, Giorgio Valentini: A stability-based algorithm to validate hierarchical clusters of genes. IJKESDP 1(4): 318-330 (2009)

Giulio Pavesi, Giorgio Valentini: Classification of co-expressed genes from DNA regulatory regions. Information Fusion 10(3): 233-241 (2009)

Giorgio Valentini: True Path Rule Hierarchical Ensembles. MCS 2009: 232-241

Matteo Re, Giorgio Valentini: Ensemble Based Data Fusion for Gene Function Prediction. MCS 2009: 448-457

Matteo Re, Giorgio Valentini: Comparing early and late data fusion methods for gene function prediction. WIRN 2009: 197-207

Matteo Re, Giorgio Valentini: Prediction of Gene Function Using Ensembles of SVMs and Heterogeneous Data Sources. Applications of Supervised and Unsupervised Ensemble Methods 2009: 79-91

Giorgio Valentini, Nicolò Cesa-Bianchi: HCGene: a software tool to support the hierarchical classification of genes. Bioinformatics 24(5): 729-731 (2008)

Alberto Bertoni, Giorgio Valentini: Discovering multi-level structures in bio-molecular data through the Bernstein inequality. BMC Bioinformatics 9(S-2) (2008)

Francesca Ruffino, Marco Muselli, Giorgio Valentini: Gene expression modeling through positive boolean functions. Int. J. Approx. Reasoning 47(1): 97-108 (2008)

Alberto Bertoni, Giorgio Valentini: Unsupervised Stability-Based Ensembles to Discover Reliable Structures in Complex Bio-molecular Data. CIBB 2008: 25-43

Oleg Okun, Giorgio Valentini: Dataset complexity can help to generate accurate ensembles of k-nearest neighbors. IJCNN 2008: 450-457

Roberto Avogadri, Matteo Brioschi, Francesca Ruffino, Fulvia Ferrazzi, Alessandro Beghini, Giorgio Valentini: An Algorithm to Assess the Reliability of Hierarchical Clusters in Gene Expression Data. KES (3) 2008: 764-770

Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini: Classification of DNA microarray data with Random Projection Ensembles of Polynomial SVMs. WIRN 2008: 60-66

Giorgio Valentini: Mosclust: a software library for discovering significant structures in bio-molecular data. Bioinformatics 23(3): 387-389 (2007)

Alberto Bertoni, Giorgio Valentini: Model order selection for bio-molecular data clustering. BMC Bioinformatics 8(S-2) (2007)

Alberto Bertoni, Giorgio Valentini: Discovering Significant Structures in Clustered Bio-molecular Data Through the Bernstein Inequality. KES (3) 2007: 886-891

Roberto Avogadri, Giorgio Valentini: Fuzzy Ensemble Clustering for DNA Microarray Data Analysis. WILF 2007: 537-543

Alberto Bertoni, Giorgio Valentini: Randomized maps for assessing the reliability of patients clusters in DNA microarray data analyses. Artificial Intelligence in Medicine 37(2): 85-109 (2006)

Giorgio Valentini: Clusterv: a tool for assessing the reliability of clusters discovered in DNA microarray data. Bioinformatics 22(3): 369-370 (2006)

Giorgio Valentini, Francesca Ruffino: Characterization of lung tumor subtypes through gene expression cluster validity assessment. ITA 40(2): 163-176 (2006)

Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini: Bio-molecular cancer prediction with random subspace ensembles of support vector machines. Neurocomputing 63: 535-539 (2005)

Paola Campadelli, Elena Casiraghi, Giorgio Valentini: Support vector machines for candidate nodules classification. Neurocomputing 68: 281-288 (2005)

Giorgio Valentini: An experimental bias-variance analysis of SVM ensembles based on resampling techniques. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(6): 1252-1271 (2005)

Paola Campadelli, Elena Casiraghi, Giorgio Valentini: Lung nodules detection and classification. ICIP (1) 2005: 1117-1120

Francesca Ruffino, Marco Muselli, Giorgio Valentini: Biological Specifications for a Synthetic Gene Expression Data Generation Model. WILF 2005: 277-283

Alberto Bertoni, Giorgio Valentini: Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms. WIRN/NAIS 2005: 31-37

Giorgio Valentini, Marco Muselli, Francesca Ruffino: Cancer recognition with bagged ensembles of support vector machines. Neurocomputing 56: 461-466 (2004)

Francesco Masulli, Giorgio Valentini: An experimental analysis of the dependence among codeword bit errors in ECOC learning machines. Neurocomputing 57: 189-214 (2004)

Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods. Journal of Machine Learning Research 5: 725-775 (2004)

Francesco Masulli, Giorgio Valentini: Effectiveness of error correcting output coding methods in ensemble and monolithic learning machines. Pattern Anal. Appl. 6(4): 285-300 (2004)

Giorgio Valentini: Random Aggregated and Bagged Ensembles of SVMs: An Empirical Bias?Variance Analysis. Multiple Classifier Systems 2004: 263-272

Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini: Feature Selection Combined with Random Subspace Ensemble for Gene Expression Based Diagnosis of Malignancies. WIRN 2004: 29-35

Giorgio Valentini, Thomas G. Dietterich: Low Bias Bagged Support Vector Machines. ICML 2003: 752-759

Giorgio Valentini: An Application of Low Bias Bagged SVMs to the Classification of Heterogeneous Malignant Tissues. WIRN 2003: 316-321

Giorgio Valentini: Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles. Artificial Intelligence in Medicine 26(3): 281-304 (2002)

Giorgio Valentini, Francesco Masulli: NEURObjects: an object-oriented library for neural network development. Neurocomputing 48(1-4): 623-646 (2002)

Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis and Ensembles of SVM. Multiple Classifier Systems 2002: 222-231

Francesco Masulli, Matteo Pardo, Giorgio Sberveglieri, Giorgio Valentini: Boosting and Classification of Electronic Nose Data. Multiple Classifier Systems 2002: 262-271

Giorgio Valentini, Francesco Masulli: Ensembles of Learning Machines. WIRN 2002: 3-22

Francesco Masulli, Giorgio Valentini: Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis. Multiple Classifier Systems 2001: 158-167

Francesco Masulli, Giorgio Valentini: Parallel Non Linear Dichotomizers. IJCNN (2) 2000: 29-36

Francesco Masulli, Giorgio Valentini: Comparing decomposition methods for classification. KES 2000: 788-791

Francesco Masulli, Giorgio Valentini: Effectiveness of Error Correcting Output Codes in Multiclass Learning Problems. Multiple Classifier Systems 2000: 107-116

Giorgio Valentini, Francesco Masulli: NEURObjects: A Set of Library Classes for Neural Networks Development. IIA/SOCO 1999