Data Cleaning and Semantic Improvement in Biological Databases. - Daniele Apiletti; Giulia Bruno; Elisa Ficarra; Elena Baralis (J. Integr. Bioinform., 2006)

SAPhyRA: Stream Analysis for Physiological Risk Assessment. - Daniele Apiletti; Elena Baralis; Giulia Bruno; Tania Cerquitelli (CBMS, 2007)

Generalized association rules to support Network Digest analysis. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Vincenzo D'Elia (SEBD, 2008)

Real-Time Individuation of Global Unsafe Anomalies and Alarm Activation. - Daniele Apiletti; Elena Baralis; Giulia Bruno; Tania Cerquitelli (Intelligent Techniques and Tools for Novel System Architectures, 2008)

Characterizing network traffic by means of the NetMine framework. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Vincenzo D'Elia (Comput. Networks, 2009)

Real-Time Analysis of Physiological Data to Support Medical Applications. - Daniele Apiletti; Elena Baralis; Giulia Bruno; Tania Cerquitelli (IEEE Trans. Inf. Technol. Biomed., 2009)

Extraction of Constraints from Biological Data. - Daniele Apiletti; Giulia Bruno; Elisa Ficarra; Elena Baralis (Biomedical Data and Applications, 2009)

Energy-saving models for wireless sensor networks. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli (Knowl. Inf. Syst., 2011)

MaskedPainter: Feature selection for microarray data analysis. - Daniele Apiletti; Elena Baralis; Giulia Bruno; Alessandro Fiori (Intell. Data Anal., 2012)

Desidoo, a Big-Data Application to Join the Online and Real-World Marketplaces. - Daniele Apiletti; Fabio Forno (ADBIS (2), 2013)

Association Rule Mining as a Cloud-Based Service. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Silvia Chiusano; Luigi Grimaudo (SEBD, 2013)

SeaRum: A Cloud-Based Service for Association Rule Mining. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Silvia Chiusano; Luigi Grimaudo (TrustCom/ISPA/IUCC, 2013)

A Review of Scalable Approaches for Frequent Itemset Mining. - Daniele Apiletti; Paolo Garza; Fabio Pulvirenti (ADBIS (Short Papers and Workshops), 2015)

Energy Signature Analysis: Knowledge at Your Fingertips. - Andrea Acquaviva; Daniele Apiletti; Antonio Attanasio; Elena Baralis; Lorenzo Bottaccioli; Federico Boni Castagnetti; Tania Cerquitelli; Silvia Chiusano; Enrico Macii; Dario Martellacci; Edoardo Patti (BigData Congress, 2015)

Enhancing Energy Awareness Through the Analysis of Thermal Energy Consumption. - Andrea Acquaviva; Daniele Apiletti; Antonio Attanasio; Elena Baralis; Federico Boni Castagnetti; Tania Cerquitelli; Silvia Chiusano; Enrico Macii; Dario Martellacci; Edoardo Patti (EDBT/ICDT Workshops, 2015)

PaMPa-HD: A Parallel MapReduce-Based Frequent Pattern Miner for High-Dimensional Data. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Paolo Garza; Pietro Michiardi; Fabio Pulvirenti (ICDM Workshops, 2015)

BAC: A Bagged Associative Classifier for Big Data Frameworks. - Luca Venturini; Paolo Garza; Daniele Apiletti (ADBIS (Short Papers and Workshops), 2016)

SaFe-NeC: A scalable and flexible system for network data characterization. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Paolo Garza; Luca Venturini (NOMS, 2016)

SeLINA: A Self-Learning Insightful Network Analyzer. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Paolo Garza; Danilo Giordano; Marco Mellia; Luca Venturini (IEEE Trans. Netw. Serv. Manag., 2016)

A Parallel MapReduce Algorithm to Efficiently Support Itemset Mining on High Dimensional Data. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Paolo Garza; Fabio Pulvirenti; Pietro Michiardi (Big Data Res., 2017)

Frequent Itemsets Mining for Big Data: A Comparative Analysis. - Daniele Apiletti; Elena Baralis; Tania Cerquitelli; Paolo Garza; Fabio Pulvirenti; Luca Venturini (Big Data Res., 2017)

iSTEP, an Integrated Self-Tuning Engine for Predictive Maintenance in Industry 4.0. - Daniele Apiletti; Claudia Barberis; Tania Cerquitelli; Alberto Macii; Enrico Macii; Massimo Poncino; Francesco Ventura (ISPA/IUCC/BDCloud/SocialCom/SustainCom, 2018)

PREMISES, a Scalable Data-Driven Service to Predict Alarms in Slowly-Degrading Multi-Cycle Industrial Processes. - Stefano Proto; Francesco Ventura; Daniele Apiletti; Tania Cerquitelli; Elena Baralis; Enrico Macii; Alberto Macii (BigData Congress, 2019)

A New Unsupervised Predictive-Model Self-Assessment Approach That SCALEs. - Francesco Ventura; Stefano Proto; Daniele Apiletti; Tania Cerquitelli; Simone Panicucci; Elena Baralis; Enrico Macii; Alberto Macii (BigData Congress, 2019)

Towards a real-time unsupervised estimation of predictive model degradation. - Tania Cerquitelli; Stefano Proto; Francesco Ventura; Daniele Apiletti; Elena Baralis (BIRTE, 2019)

Transparently Mining Data from a Medium-voltage Distribution Network: A Prognostic-diagnostic Analysis. - Matteo Nisi; Daniela Renga; Daniele Apiletti; Danilo Giordano; Tao Huang 002; Yang Zhang 069; Marco Mellia; Elena Baralis (EDBT/ICDT Workshops, 2019)

Automating concept-drift detection by self-evaluating predictive model degradation. - Tania Cerquitelli; Stefano Proto; Francesco Ventura; Daniele Apiletti; Elena Baralis (CoRR, 2019)

Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images. - Simone Monaco; Andrea Pasini; Daniele Apiletti; Luca Colomba; Paolo Garza; Elena Baralis (IEEE BigData, 2020)

DSLE: A Smart Platform for Designing Data Science Competitions. - Giuseppe Attanasio; Flavio Giobergia; Andrea Pasini; Francesco Ventura; Elena Baralis; Luca Cagliero; Paolo Garza; Daniele Apiletti; Tania Cerquitelli; Silvia Chiusano (COMPSAC, 2020)

Evaluating espresso coffee quality by means of time-series feature engineering. - Daniele Apiletti; Eliana Pastor; Riccardo Callà; Elena Baralis (EDBT/ICDT Workshops, 2020)

REDTag: A Predictive Maintenance Framework for Parcel Delivery Services. - Stefano Proto; Evelina Di Corso; Daniele Apiletti; Luca Cagliero; Tania Cerquitelli; Giovanni Malnati; Davide Mazzucchi (IEEE Access, 2020)

Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis. - Daniela Renga; Daniele Apiletti; Danilo Giordano; Matteo Nisi; Tao Huang 002; Yang Zhang 069; Marco Mellia; Elena Baralis (Computing, 2020)

Forecasting: theory and practice. - Fotios Petropoulos; Daniele Apiletti; Vassilios Assimakopoulos; Mohamed Zied Babai; Devon K. Barrow; Souhaib Ben Taieb; Christoph Bergmeir; Ricardo J. Bessa; Jakub Bijak; John E. Boylan; Jethro Browell; Claudio Carnevale; et al. (CoRR, 2020)

Effective video hyperlinking by means of enriched feature sets and monomodal query combinations. - Mohammad Reza Kavoosifar; Daniele Apiletti; Elena Baralis; Paolo Garza; Benoit Huet (Int. J. Multim. Inf. Retr., 2020)

Cyst segmentation on kidney tubules by means of U-Net deep-learning models. - Simone Monaco; Nicole Bussola; Sara Buttò; Diego Sona; Daniele Apiletti; Giuseppe Jurman; Elisa Viola; Marco Chierici; Christodoulos Xinaris; Vincenzo Viola (IEEE BigData, 2021)

Double-Step deep learning framework to improve wildfire severity classification. - Simone Monaco; Andrea Pasini; Daniele Apiletti; Luca Colomba; Alessandro Farasin; Paolo Garza; Elena Baralis (EDBT/ICDT Workshops, 2021)

Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features. - Francesco Ventura; Salvatore Greco; Daniele Apiletti; Tania Cerquitelli (CoRR, 2021)

Enhancing manufacturing intelligence through an unsupervised data-driven methodology for cyclic industrial processes. - Tania Cerquitelli; Francesco Ventura; Daniele Apiletti; Elena Baralis; Enrico Macii; Massimo Poncino (Expert Syst. Appl., 2021)

Experimental Comparison of Theory-Guided Deep Learning Algorithms. - Simone Monaco; Daniele Apiletti (ADBIS (Short Papers), 2022)

A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. - Luca Colomba; Alessandro Farasin; Simone Monaco; Salvatore Greco; Paolo Garza; Daniele Apiletti; Elena Baralis; Tania Cerquitelli (CIKM, 2022)

Exploring waste-collection fleet data: challenges in a real-world use case. - Simone Monaco; Paolo Bethaz; Daniele Apiletti; Fabrizio Pio Baldini; Carlo Caso; Tania Cerquitelli (EDBT/ICDT Workshops, 2022)

Trusting deep learning natural-language models via local and global explanations. - Francesco Ventura; Salvatore Greco; Daniele Apiletti; Tania Cerquitelli (Knowl. Inf. Syst., 2022)

Satellite Burned Area Dataset. - Luca Colomba; Alessandro Farasin; Simone Monaco; Salvatore Greco; Paolo Garza; Daniele Apiletti; Elena Baralis; Tania Cerquitelli (Zenodo, 2022)

Combining fault-tolerant persistence and low-latency streaming access to binary data for AI models. - Gabriele Scaffidi Militone; Daniele Apiletti; Giovanni Malnati (IEEE Big Data, 2023)

ba휌tti at GeoLingIt: Beyond Boundaries, Enhancing Geolocation Prediction and Dialect Classification on Social Media in Italy. - Alkis Koudounas; Flavio Giobergia; Irene Benedetto; Simone Monaco; Luca Cagliero; Daniele Apiletti; Elena Baralis (EVALITA, 2023)

Lorentz-Invariant Augmentation for High-Energy Physics Deep Learning Models. - Simone Monaco; Sebastiano Barresi; Daniele Apiletti (PKDD/ECML Workshops (3), 2023)

Level Up Your Tutorials: VLMs for Game Tutorials Quality Assessment. - Daniele Rege Cambrin; Gabriele Scaffidi Militone; Luca Colomba; Giovanni Malnati; Daniele Apiletti; Paolo Garza (ECCV Workshops (2), 2024)

DriftLens: A Concept Drift Detection Tool. - Salvatore Greco; Bartolomeo Vacchetti; Daniele Apiletti; Tania Cerquitelli (EDBT, 2024)

Unsupervised Concept Drift Detection from Deep Learning Representations in Real-time. - Salvatore Greco; Bartolomeo Vacchetti; Daniele Apiletti; Tania Cerquitelli (CoRR, 2024)

Uncertainty-aware segmentation for rainfall prediction post processing. - Simone Monaco; Luca Monaco; Daniele Apiletti (CoRR, 2024)

Deep Probability Segmentation: Are segmentation models probability estimators? - Simone Fassio; Simone Monaco; Daniele Apiletti (CoRR, 2024)

Hermes, a low-latency transactional storage for binary data streams from remote devices. - Gabriele Scaffidi Militone; Daniele Apiletti; Giovanni Malnati (Data Knowl. Eng., 2024)

Explaining deep convolutional models by measuring the influence of interpretable features in image classification. - Francesco Ventura; Salvatore Greco; Daniele Apiletti; Tania Cerquitelli (Data Min. Knowl. Discov., 2024)

Quantify production planning efficiency through predictive modeling in manufacturing systems. - Simone Monaco; Daniele Apiletti; Andrea Francica; Tania Cerquitelli (Comput. Ind. Eng., 2025)

Uncertainty-aware methods for enhancing rainfall prediction with deep-learning based post-processing segmentation. - Simone Monaco; Luca Monaco; Daniele Apiletti; Roberto Cremonini 001; Secondo Barbero (Comput. Geosci., 2025)