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ORCIDDonato Malerba
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- affiliation: University of Bari Aldo Moro, Italy
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2020 – today
- 2024
[j87]Luca De Rose
, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
VINCENT: Cyber-threat detection through vision transformers and knowledge distillation. Comput. Secur. 144: 103926 (2024)- [j86]Muhammad Imran, Annalisa Appice, Donato Malerba:
Evaluating Realistic Adversarial Attacks against Machine Learning Models for Windows PE Malware Detection. Future Internet 16(5): 168 (2024) - [j85]Vincenzo Pasquadibisceglie, Annalisa Appice, Giuseppe Ieva, Donato Malerba:
TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments. J. Intell. Inf. Syst. 62(3): 705-733 (2024) - [j84]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
PANACEA: a neural model ensemble for cyber-threat detection. Mach. Learn. 113(8): 5379-5422 (2024) - [j83]Corrado Loglisci, Donato Malerba, Saverio Pascazio:
Quarta: quantum supervised and unsupervised learning for binary classification in domain-incremental learning. Quantum Mach. Intell. 6(2): 68 (2024) - [j82]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
A Deep Semantic Segmentation Approach to Map Forest Tree Dieback in Sentinel-2 Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 17: 17075-17086 (2024) - [j81]Vincenzo Pasquadibisceglie, Raffaele Scaringi, Annalisa Appice, Giovanna Castellano, Donato Malerba:
${\sf PROPHET}$PROPHET: Explainable Predictive Process Monitoring With Heterogeneous Graph Neural Networks. IEEE Trans. Serv. Comput. 17(6): 4111-4124 (2024) - [c249]Vincenzo Pasquadibisceglie, Annalisa Appice, Donato Malerba:
LUPIN: A LLM Approach for Activity Suffix Prediction in Business Process Event Logs. ICPM 2024: 1-8 - [c248]Giuseppina Andresini, Annalisa Appice, Dino Ienco, Donato Malerba, Vito Recchia:
Potential of Spectral-Spatial Analysis to Map Forest Tree Dieback Due to Bark Beetle Hotspots in Sentinel-2 Images. IGARSS 2024: 5227-5230 - [c247]Vincenzo Pasquadibisceglie, Donato Lucente, Donato Malerba:
A Stream Data Mining Approach to Handle Concept Drifts in Process Discovery. ISMIS 2024: 136-145 - [c246]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Enhancing Cyber-threat detection coupling Deep Neural Ensemble Learning with XAI. Ital-IA 2024: 182-187 - [c245]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Leveraging Sentinel-2 time series for bark beetle-induced forest dieback inventory. SAC 2024: 875-882 - [c244]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Enhancing Next Activity Prediction with Adversarial Training of Vision Transformers. SEBD 2024: 349-358 - [e12]Maurizio Atzori, Paolo Ciaccia, Michelangelo Ceci, Federica Mandreoli, Donato Malerba, Manuela Sanguinetti, Antonio Pellicani, Federico Motta:
Proceedings of the 32nd Symposium of Advanced Database Systems, Villasimius, Italy, June 23rd to 26th, 2024. CEUR Workshop Proceedings 3741, CEUR-WS.org 2024 [contents] - 2023
- [j80]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
DARWIN : An online deep learning approach to handle concept drifts in predictive process monitoring. Eng. Appl. Artif. Intell. 123(Part C): 106461 (2023) - [j79]Giuseppina Andresini, Annalisa Appice, Dino Ienco, Donato Malerba:
SENECA: Change detection in optical imagery using Siamese networks with Active-Transfer Learning. Expert Syst. Appl. 214: 119123 (2023) - [j78]Filippo Lorè, Pierpaolo Basile, Annalisa Appice, Marco de Gemmis, Donato Malerba, Giovanni Semeraro:
An AI framework to support decisions on GDPR compliance. J. Intell. Inf. Syst. 61(2): 541-568 (2023) - [j77]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
$\mathsf{SILVIA}$: An eXplainable Framework to Map Bark Beetle Infestation in Sentinel-2 Images. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 16: 10050-10066 (2023) - [j76]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Nicola Fiorentino, Donato Malerba:
STARDUST: A Novel Process Mining Approach to Discover Evolving Models From Trace Streams. IEEE Trans. Serv. Comput. 16(4): 2970-2984 (2023) - [c243]Giuseppina Andresini, Annalisa Appice, Pasquale Ardimento, Andrea Antonio Brunetta, Antonio Giuseppe Doronzo, Giuseppe Ieva, Francesco Luce, Donato Malerba, Vincenzo Pasquadibisceglie:
CENTAURO: An Explainable AI Approach for Customer Loyalty Prediction in Retail Sector. AI*IA 2023: 205-217 - [c242]Corrado Loglisci, Donato Malerba:
Coupling quantum classification and quantum distance estimation in continual learning. AIQxQIA@AI*IA 2023 - [c241]Giuseppina Andresini, Annalisa Appice, Roberto Gasbarro, Donato Malerba:
GLORIA: A Graph Convolutional Network-Based Approach for Review Spam Detection. DS 2023: 111-125 - [c240]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
PANACEA: A Neural Model Ensemble for Cyber-Threat Detection. DSAA 2023: 1-2 - [c239]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Striving for Simplicity in Deep Neural Models Trained for Malware Detection. PKDD/ECML Workshops (3) 2023: 529-540 - [c238]Corrado Loglisci, Ivan Diliso, Donato Malerba:
A Hybrid Quantum-Classical Framework for Binary Classification in Online Learning. SEBD 2023: 88-99 - [e11]Marco Anisetti, Angela Bonifati, Nicola Bena, Claudio A. Ardagna, Donato Malerba:
Proceedings of the 1st Italian Conference on Big Data and Data Science (itaDATA 2022), Milan, Italy, September 20-21, 2022. CEUR Workshop Proceedings 3340, CEUR-WS.org 2023 [contents] - 2022
- [j75]Giuseppina Andresini, Annalisa Appice, Francesco Paolo Caforio, Donato Malerba, Gennaro Vessio:
ROULETTE: A neural attention multi-output model for explainable Network Intrusion Detection. Expert Syst. Appl. 201: 117144 (2022) - [j74]Giuseppina Andresini, Annalisa Appice, Daniele Iaia, Donato Malerba, Nicolò Taggio, Antonello Aiello:
Leveraging autoencoders in change vector analysis of optical satellite images. J. Intell. Inf. Syst. 58(3): 433-452 (2022) - [j73]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
A Multi-View Deep Learning Approach for Predictive Business Process Monitoring. IEEE Trans. Serv. Comput. 15(4): 2382-2395 (2022) - [c237]Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Public Transport and Air Pollution Analysis. IEEE Big Data 2022: 2867-2874 - [c236]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
An XAI-based adversarial training approach for cyber-threat detection. DASC/PiCom/CBDCom/CyberSciTech 2022: 1-8 - [c235]Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
XAI to Explore Robustness of Features in Adversarial Training for Cybersecurity. ISMIS 2022: 117-126 - [c234]Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Physical Threat Intelligence. itaDATA 2022: 39-50 - [c233]Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Physical Threat Intelligence. PKDD/ECML Workshops (1) 2022: 281-292 - [c232]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
A multi-view deep learning approach for predictive business processes monitoring. SERVICES 2022: 26 - 2021
- [j72]Giuseppina Andresini, Annalisa Appice, Luca De Rose, Donato Malerba:
GAN augmentation to deal with imbalance in imaging-based intrusion detection. Future Gener. Comput. Syst. 123: 108-127 (2021) - [j71]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Autoencoder-based deep metric learning for network intrusion detection. Inf. Sci. 569: 706-727 (2021) - [j70]Marjana Prifti Skenduli, Marenglen Biba, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
Mining emotion-aware sequential rules at user-level from micro-blogs. J. Intell. Inf. Syst. 57(2): 369-394 (2021) - [j69]Annalisa Appice, Angelo Cannarile, Antonella Falini, Donato Malerba, Francesca Mazzia, Cristiano Tamborrino:
Leveraging colour-based pseudo-labels to supervise saliency detection in hyperspectral image datasets. J. Intell. Inf. Syst. 57(3): 423-446 (2021) - [j68]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Nearest cluster-based intrusion detection through convolutional neural networks. Knowl. Based Syst. 216: 106798 (2021) - [c231]Giuseppina Andresini, Annalisa Appice, Domenico Dell'Olio, Donato Malerba:
Siamese Networks with Transfer Learning for Change Detection in Sentinel-2 Images. AI*IA 2021: 478-489 - [c230]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Leveraging Multi-view Deep Learning for Next Activity Prediction. ITBPM@BPM 2021: 1-6 - [c229]Giuseppina Andresini, Annalisa Appice, Corrado Loglisci, Vincenzo Belvedere, Domenico Redavid, Donato Malerba:
A Network Intrusion Detection System for Concept Drifting Network Traffic Data. DS 2021: 111-121 - [c228]Francesco Paolo Caforio, Giuseppina Andresini, Gennaro Vessio, Annalisa Appice, Donato Malerba:
Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems. DS 2021: 385-400 - [c227]Vincenzo Pasquadibisceglie, Giovanna Castellano, Annalisa Appice, Donato Malerba:
FOX: a neuro-Fuzzy model for process Outcome prediction and eXplanation. ICPM 2021: 112-119 - [c226]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
A Two-Step Network Intrusion Detection System for Multi-Class Classification (Discussion Paper). SEBD 2021: 259-266 - [e10]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e9]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - 2020
- [j67]Annalisa Appice, Yulia R. Gel, Iliyan Iliev, Vyacheslav Lyubchich, Donato Malerba:
A Multi-Stage Machine Learning Approach to Predict Dengue Incidence: A Case Study in Mexico. IEEE Access 8: 52713-52725 (2020) - [j66]Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Multi-Channel Deep Feature Learning for Intrusion Detection. IEEE Access 8: 53346-53359 (2020) - [j65]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba, Giuseppe Modugno:
ORANGE: Outcome-Oriented Predictive Process Monitoring Based on Image Encoding and CNNs. IEEE Access 8: 184073-184086 (2020) - [j64]Annalisa Appice, Pietro Guccione, Emilio Acciaro, Donato Malerba:
Detecting salient regions in a bi-temporal hyperspectral scene by iterating clustering and classification. Appl. Intell. 50(10): 3179-3200 (2020) - [j63]Angelo Impedovo, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
Condensed representations of changes in dynamic graphs through emerging subgraph mining. Eng. Appl. Artif. Intell. 94: 103830 (2020) - [j62]Annalisa Appice, Giuseppina Andresini, Donato Malerba:
Clustering-Aided Multi-View Classification: A Case Study on Android Malware Detection. J. Intell. Inf. Syst. 55(1): 1-26 (2020) - [j61]Angelo Impedovo, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
jKarma: A highly-modular framework for pattern-based change detection on evolving data. Knowl. Based Syst. 192: 105303 (2020) - [j60]Gianvito Pio, Michelangelo Ceci, Francesca Prisciandaro, Donato Malerba:
Exploiting causality in gene network reconstruction based on graph embedding. Mach. Learn. 109(6): 1231-1279 (2020) - [c225]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Predictive Process Mining Meets Computer Vision. BPM (Forum) 2020: 176-192 - [c224]Annalisa Appice, Pasquale Ardimento, Donato Malerba, Giuseppe Modugno, Diego Marra, Marco Mottola:
Training in a Virtual Learning Environment: A Process Mining Approach. EAIS 2020: 1-8 - [c223]Antonella Falini, Graziano Castellano, Cristiano Tamborrino, Francesca Mazzia, Rosa Maria Mininni, Annalisa Appice, Donato Malerba:
Saliency Detection for Hyperspectral Images via Sparse-Non Negative-Matrix-Factorization and novel Distance Measures*. EAIS 2020: 1-8 - [c222]Annalisa Appice, Francesco Lomuscio, Antonella Falini, Cristiano Tamborrino, Francesca Mazzia, Donato Malerba:
Saliency Detection in Hyperspectral Images Using Autoencoder-Based Data Reconstruction. ISMIS 2020: 161-170 - [c221]Corrado Loglisci, Marco Zappatore, Antonella Longo, Mario A. Bochicchio, Donato Malerba:
Leveraging Machine Learning in IoT to Predict the Trustworthiness of Mobile Crowd Sensing Data. ISMIS 2020: 235-244 - [c220]Antonella Falini, Cristiano Tamborrino, Graziano Castellano, Francesca Mazzia, Rosa Maria Mininni, Annalisa Appice, Donato Malerba:
Novel Reconstruction Errors for Saliency Detection in Hyperspectral Images. LOD (1) 2020: 113-124 - [c219]Matteo Greco, Michele Spagnoletta, Annalisa Appice, Donato Malerba:
Applying Machine Learning to Predict Closing Prices in Stock Market: A Case Study. MIDAS@PKDD/ECML 2020: 32-39 - [c218]Angelo Impedovo, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
jKarma: A Highly-Modular Framework for Pattern-Based Change Detection on Evolving Data. SEBD 2020: 343-350 - [p9]Angelo Impedovo, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
Exploiting Pattern Set Dissimilarity for Detecting Changes in Communication Networks. Complex Pattern Mining 2020: 137-152 - [p8]Giuseppina Andresini, Annalisa Appice, Donato Malerba:
Dealing with Class Imbalance in Android Malware Detection by Cascading Clustering and Classification. Complex Pattern Mining 2020: 173-187 - [e8]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents]
2010 – 2019
- 2019
- [j59]Marco Zappatore, Corrado Loglisci, Antonella Longo, Mario A. Bochicchio, Lucia Vaira, Donato Malerba:
Trustworthiness of Context-Aware Urban Pollution Data in Mobile Crowd Sensing. IEEE Access 7: 154141-154156 (2019) - [j58]Michelangelo Ceci, Roberto Corizzo, Donato Malerba, Aleksandra Rashkovska:
Spatial autocorrelation and entropy for renewable energy forecasting. Data Min. Knowl. Discov. 33(3): 698-729 (2019) - [j57]Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba:
DENCAST: distributed density-based clustering for multi-target regression. J. Big Data 6: 43 (2019) - [c217]Annalisa Appice, Nicola Di Mauro, Donato Malerba:
Leveraging Shallow Machine Learning to Predict Business Process Behavior. SCC 2019: 184-188 - [c216]Corrado Loglisci, Donato Malerba:
Periodicity Detection of Emotional Communities in Microblogging. AI*IA 2019: 558-571 - [c215]Roberto Corizzo, Michelangelo Ceci, Donato Malerba:
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector. BigData Congress 2019: 55-63 - [c214]Giuseppina Andresini, Annalisa Appice, Nicola Di Mauro, Corrado Loglisci, Donato Malerba:
Exploiting the Auto-Encoder Residual Error for Intrusion Detection. EuroS&P Workshops 2019: 281-290 - [c213]Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, Donato Malerba:
Using Convolutional Neural Networks for Predictive Process Analytics. ICPM 2019: 129-136 - [c212]Annalisa Appice, Nicola Di Mauro, Francesco Lomuscio, Donato Malerba:
Empowering Change Vector Analysis with Autoencoding in Bi-temporal Hyperspectral Images. MACLEAN@PKDD/ECML 2019 - [c211]Corrado Loglisci, Angelo Impedovo, Michelangelo Ceci, Donato Malerba:
Mining Microscopic and Macroscopic Changes in Network Data Streams (Discussion Paper). SEBD 2019 - 2018
- [j56]Sonja Pravilovic, Annalisa Appice, Donato Malerba:
Leveraging correlation across space and time to interpolate geophysical data via CoKriging. Int. J. Geogr. Inf. Sci. 32(1): 191-212 (2018) - [j55]Gianvito Pio, Francesco Serafino, Donato Malerba, Michelangelo Ceci:
Multi-type clustering and classification from heterogeneous networks. Inf. Sci. 425: 107-126 (2018) - [j54]Annalisa Appice, Corrado Loglisci, Donato Malerba:
Active learning via collective inference in network regression problems. Inf. Sci. 460-461: 293-317 (2018) - [j53]Corrado Loglisci, Michelangelo Ceci, Angelo Impedovo, Donato Malerba:
Mining microscopic and macroscopic changes in network data streams. Knowl. Based Syst. 161: 294-312 (2018) - [c210]Corrado Loglisci, Giuseppina Andresini, Angelo Impedovo, Donato Malerba:
Analyzing Microblogging Posts for Tracking Collective Emotional Trajectories. AI*IA 2018: 123-135 - [c209]Domenico Redavid, Roberto Corizzo, Donato Malerba:
An OWL Ontology for Supporting Semantic Services in Big Data Platforms. BigData Congress 2018: 228-231 - [c208]Domenico Redavid, Donato Malerba, Beniamino Di Martino, Antonio Esposito, Claudio A. Ardagna, Valerio Bellandi, Paolo Ceravolo, Ernesto Damiani:
Semantic Support for Model Based Big Data Analytics-as-a-Service (MBDAaaS). CISIS 2018: 1012-1021 - [c207]Marjana Prifti Skenduli, Corrado Loglisci, Michelangelo Ceci, Marenglen Biba, Donato Malerba:
An Empirical Evaluation of Sequential Pattern Mining Algorithms. EIDWT 2018: 615-626 - [c206]Ernesto Damiani, Gabriele Gianini, Michelangelo Ceci, Donato Malerba:
Toward IoT-Friendly Learning Models. ICDCS 2018: 1284-1289 - [c205]Michelangelo Ceci, Michele Spagnoletta, Pasqua Fabiana Lanotte, Donato Malerba:
Distributed Learning of Process Models for Next Activity Prediction. IDEAS 2018: 278-282 - [c204]Marjana Prifti Skenduli, Marenglen Biba, Corrado Loglisci, Michelangelo Ceci, Donato Malerba:
User-Emotion Detection Through Sentence-Based Classification Using Deep Learning: A Case-Study with Microblogs in Albanian. ISMIS 2018: 258-267 - [c203]Annalisa Appice, Antonietta Lanza, Donato Malerba:
Handling Multi-scale Data via Multi-target Learning for Wind Speed Forecasting. ISMIS 2018: 357-366 - [c202]Annalisa Appice, Antonietta Lanza, Donato Malerba:
Wind Speed Forecasting via Structured Output Learning. SEBD 2018 - [p7]Annalisa Appice, Michelangelo Ceci, Donato Malerba:
Relational Data Mining in the Era of Big Data. A Comprehensive Guide Through the Italian Database Research 2018: 323-339 - 2017
- [j52]Sonja Pravilovic, Massimo Bilancia, Annalisa Appice, Donato Malerba:
Using multiple time series analysis for geosensor data forecasting. Inf. Sci. 380: 31-52 (2017) - [j51]Annalisa Appice, Pietro Guccione, Donato Malerba:
A novel spectral-spatial co-training algorithm for the transductive classification of hyperspectral imagery data. Pattern Recognit. 63: 229-245 (2017) - [j50]Corrado Loglisci, Donato Malerba:
Leveraging temporal autocorrelation of historical data for improving accuracy in network regression. Stat. Anal. Data Min. 10(1): 40-53 (2017) - [j49]Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Donato Malerba, Aleksandra Rashkovska:
Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction? IEEE Trans. Ind. Informatics 13(3): 956-966 (2017) - [c201]Annalisa Appice, Sonja Pravilovic, Donato Malerba, Antonietta Lanza:
Sampling Training Data for Accurate Hyperspectral Image Classification via Tree-Based Spatial Clustering. AI*IA 2017: 309-320 - [c200]Gianvito Pio, Michelangelo Ceci, Francesca Prisciandaro, Donato Malerba:
LOCANDA: Exploiting Causality in the Reconstruction of Gene Regulatory Networks. DS 2017: 283-297 - [c199]Pasqua Fabiana Lanotte, Fabio Fumarola, Donato Malerba, Michelangelo Ceci:
Exploiting Web Sites Structural and Content Features for Web Pages Clustering. ISMIS 2017: 446-456 - [c198]Emanuele Pio Barracchia, Gianvito Pio, Donato Malerba, Michelangelo Ceci:
Identifying lncRNA-Disease Relationships via Heterogeneous Clustering. NFMCP@PKDD/ECML 2017: 35-48 - [c197]Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba:
Forecasting via Distributed Density-Based Clustering. SEBD 2017: 57 - [e7]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - 2016
- [j48]Corrado Loglisci, Annalisa Appice, Donato Malerba:
Collective regression for handling autocorrelation of network data in a transductive setting. J. Intell. Inf. Syst. 46(3): 447-472 (2016) - [j47]Fabio Fumarola, Pasqua Fabiana Lanotte, Michelangelo Ceci, Donato Malerba:
CloFAST: closed sequential pattern mining using sparse and vertical id-lists. Knowl. Inf. Syst. 48(2): 429-463 (2016) - [j46]Annalisa Appice, Pietro Guccione, Donato Malerba:
Transductive hyperspectral image classification: toward integrating spectral and relational features via an iterative ensemble system. Mach. Learn. 103(3): 343-375 (2016) - [j45]