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Gianvito Pio
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2020 – today
- 2025
- [j27]Antonio Pellicani
, Gianvito Pio
CARROT: Simultaneous prediction of anomalies from groups of correlated cryptocurrency trends. Expert Syst. Appl. 260: 125457 (2025) - 2024
- [j26]Paolo Mignone
Distributed Heterogeneous Transfer Learning. Big Data Res. 37: 100456 (2024) - [j25]Andrea Simeon
Multi-class boosting for the analysis of multiple incomplete views on microbiome data. BMC Bioinform. 25(1): 188 (2024) - [c27]Stefano Polimena
Improving the Robustness to Color Perturbations of Classification and Regression Models in the Visual Evaluation of Fruits and Vegetables. ISMIS 2024: 3-13 - [c26]Daniele Rosa
Exploiting microRNA Expression Data for the Diagnosis of Disease Conditions and the Discovery of Novel Biomarkers. ISMIS 2024: 77-86 - [c25]Annunziata D'Aversa, Gianvito Pio:
Nowcasting of the energy production of wind power plants through spatially-aware model trees. SEBD 2024: 195-204 - 2023
- [j24]Massimo Bilancia
Variational Bayes estimation of hierarchical Dirichlet-multinomial mixtures for text clustering. Comput. Stat. 38(4): 2015-2051 (2023) - [j23]Valeria Merlo
On the exploitation of the blockchain technology in the healthcare sector: A systematic review. Expert Syst. Appl. 213(Part): 118897 (2023) - [j22]Antonio Pellicani
SAIRUS: Spatially-aware identification of risky users in social networks. Inf. Fusion 92: 435-449 (2023) - [j21]Graziella De Martino
Multi-view overlapping clustering for the identification of the subject matter of legal judgments. Inf. Sci. 638: 118956 (2023) - [j20]Serena De Ruvo, Gianvito Pio
Forecasting and what-if analysis of new positive COVID-19 cases during the first three waves in Italy. Medical Biol. Eng. Comput. 61(8): 2051-2066 (2023) - [j19]Roberto Corizzo
HURI: Hybrid user risk identification in social networks. World Wide Web (WWW) 26(5): 3409-3439 (2023) - [c24]Antonio Pellicani, Gianvito Pio, Michelangelo Ceci:
A Multi-Perspective Approach for Risky User Identification in Social Networks. SEBD 2023: 665-673 - 2022
- [j18]Graziella De Martino
PRILJ: an efficient two-step method based on embedding and clustering for the identification of regularities in legal case judgments. Artif. Intell. Law 30(3): 359-390 (2022) - [j17]Gianvito Pio
Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction. Bioinform. 38(2): 487-493 (2022) - [j16]Emanuele Pio Barracchia
LP-ROBIN: Link prediction in dynamic networks exploiting incremental node embedding. Inf. Sci. 606: 702-721 (2022) - [j15]Matej Petkovic
Relational tree ensembles and feature rankings. Knowl. Based Syst. 251: 109254 (2022) - [c23]Paolo Mignone
Distributed Heterogeneous Transfer Learning for Link Prediction in the Positive Unlabeled Setting. IEEE Big Data 2022: 5536-5541 - [c22]Annunziata D'Aversa
Leveraging Spatio-Temporal Autocorrelation to Improve the Forecasting of the Energy Consumption in Smart Grids. DS 2022: 141-156 - [c21]Graziella De Martino
Identification of Paragraph Regularities in Legal Judgements Through Clustering and Textual Embedding. ISMIS 2022: 74-84 - [c20]Paolo Mignone, Gianvito Pio, Michelangelo Ceci:
Distributed Heterogeneous Transfer Learning. SEBD 2022: 351-358 - 2021
- [j14]Sibylle Hess
BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent. Data Min. Knowl. Discov. 35(6): 2542-2576 (2021) - [c19]Roberto Corizzo
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. DS 2021: 461-471 - [c18]Graziella De Martino, Gianvito Pio, Michelangelo Ceci:
A Two-Step Method based on Embedding and Clustering to Identify Regularities in Legal Case Judgements (Discussion Paper). SEBD 2021: 379-386 - 2020
- [j13]Michelangelo Ceci
ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. IEEE Access 8: 156053-156066 (2020) - [j12]Paolo Mignone
Exploiting transfer learning for the reconstruction of the human gene regulatory network. Bioinform. 36(5): 1553-1561 (2020) - [j11]Emanuele Pio Barracchia
Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering. BMC Bioinform. 21(1): 70 (2020) - [j10]Gianvito Pio
Exploiting causality in gene network reconstruction based on graph embedding. Mach. Learn. 109(6): 1231-1279 (2020) - [c17]Emanuele Pio Barracchia, Gianvito Pio, Domenica D'Elia, Michelangelo Ceci:
Prediction of New Associations between ncRNAs and Diseases Exploiting Multi-Type Hierarchical Clustering. SEBD 2020: 160-167
2010 – 2019
- 2019
- [j9]Roberto Corizzo
DENCAST: distributed density-based clustering for multi-target regression. J. Big Data 6: 43 (2019) - [c16]Paolo Mignone
Positive Unlabeled Link Prediction via Transfer Learning for Gene Network Reconstruction (Discussion Paper). SEBD 2019 - 2018
- [j8]Gianvito Pio
Multi-type clustering and classification from heterogeneous networks. Inf. Sci. 425: 107-126 (2018) - [j7]Francesco Serafino
Ensemble Learning for Multi-Type Classification in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 30(12): 2326-2339 (2018) - [c15]Paolo Mignone
Positive Unlabeled Link Prediction via Transfer Learning for Gene Network Reconstruction. ISMIS 2018: 13-23 - [c14]Francesco Serafino, Gianvito Pio, Michelangelo Ceci:
Ensemble Learning for Multi-type Classification in Heterogeneous Networks. SEBD 2018 - 2017
- [c13]Gianvito Pio
LOCANDA: Exploiting Causality in the Reconstruction of Gene Regulatory Networks. DS 2017: 283-297 - [c12]Emanuele Pio Barracchia
Identifying lncRNA-Disease Relationships via Heterogeneous Clustering. NFMCP@PKDD/ECML 2017: 35-48 - [c11]Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba:
Forecasting via Distributed Density-Based Clustering. SEBD 2017: 57 - 2016
- [c10]Francesco Serafino, Gianvito Pio, Donato Malerba, Michelangelo Ceci:
Multi-Type Classification from Heterogeneous Networks. SEBD 2016: 102-109 - [c9]Michelangelo Ceci, Gianvito Pio, Vladimir Kuzmanovski, Saso Dzeroski:
Semi-Supervised Multi-View Learning for Gene Network Reconstruction. SEBD 2016: 198-205 - 2015
- [j6]Gianvito Pio
ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks. BMC Bioinform. 16(S-9): S7 (2015) - [j5]Nicoletta Del Buono
Non-negative Matrix Tri-Factorization for co-clustering: An analysis of the block matrix. Inf. Sci. 301: 13-26 (2015) - [c8]Francesco Serafino
Hierarchical Multidimensional Classification of Web Documents with MultiWebClass. Discovery Science 2015: 236-250 - 2014
- [j4]Gianvito Pio
Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach. BMC Bioinform. 15(S-1): S4 (2014) - [j3]Gianvito Pio
Discovering Novelty Patterns from the Ancient Christian Inscriptions of Rome. ACM Journal on Computing and Cultural Heritage 7(4): 22:1-22:21 (2014) - [c7]Gianvito Pio
Mining Temporal Evolution of Entities in a Stream of Textual Documents. ISMIS 2014: 50-60 - [c6]Gianvito Pio
Network Reconstruction for the Identification of miRNA: mRNA Interaction Networks. ECML/PKDD (3) 2014: 508-511 - [c5]Gianvito Pio, Michelangelo Ceci, Domenica D'Elia, Donato Malerba:
Learning to Combine miRNA Target Predictions: a Semi-supervised Ensemble Learning Approach. SEBD 2014: 21-28 - 2013
- [j2]Gianvito Pio
A Novel Biclustering Algorithm for the Discovery of Meaningful Biological Correlations between microRNAs and their Target Genes. BMC Bioinform. 14(S-7): S8 (2013) - [j1]Piero Molino, Gianvito Pio
Fast Fuzzy Inference in Octave. Int. J. Comput. Intell. Syst. 6(2): 307-317 (2013) - [c4]Fabio Fumarola, Gianvito Pio
EDB: Knowledge Technologies for Ancient Greek and Latin Epigraphy. IRCDL 2013: 29-40 - [c3]Gianvito Pio, Michelangelo Ceci, Domenica D'Elia, Corrado Loglisci, Donato Malerba:
HOCCLUS2: A Biclustering Algorithm for the Discovery of miRNA: mRNA regulatory modules. SEBD 2013: 445-452 - 2012
- [c2]Gianvito Pio
Hierarchical and Overlapping Co-Clustering of mRNA: miRNA Interactions. ECAI 2012: 654-659 - [c1]Gianvito Pio, Michelangelo Ceci, Donato Malerba:
Mining Temporal Evolution of Criminal Behaviors. SEBD 2012: 221-232
Coauthor Index
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