Francesco Ventura

According to our database, Francesco Ventura authored at least 20 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., September, 2024

2022

Trusting deep learning natural-language models via local and global explanations.

Francesco Ventura, Salvatore Greco, Daniele Apiletti, Tania Cerquitelli

Knowl. Inf. Syst., 2022

Farming Your ML-based Query Optimizer's Food.

Robin Van De Water, Francesco Ventura, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Volker Markl

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

DataFarm: Farm Your ML-based Query Optimizer's Food! - Human-Guided Training Data Generation -.

Robin Van De Water, Francesco Ventura, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Volker Markl

Proceedings of the 12th Conference on Innovative Data Systems Research, 2022

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

Explaining the Deep Natural Language Processing by Mining Textual Interpretable Features.

Francesco Ventura, Salvatore Greco, Daniele Apiletti, Tania Cerquitelli

CoRR, 2021

Expand your Training Limits! Generating Training Data for ML-based Data Management.

Francesco Ventura, Zoi Kaoudi, Jorge-Arnulfo Quiané-Ruiz, Volker Markl

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

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

Proceedings of the 44th IEEE Annual Computers, Software, and Applications Conference, 2020

2019

What's in the box? Explaining the black-box model through an evaluation of its interpretable features.

Francesco Ventura, Tania Cerquitelli

CoRR, 2019

Automating concept-drift detection by self-evaluating predictive model degradation.

Tania Cerquitelli, Stefano Proto, Francesco Ventura, Daniele Apiletti, Elena Baralis

CoRR, 2019

Towards a real-time unsupervised estimation of predictive model degradation.

Tania Cerquitelli, Stefano Proto, Francesco Ventura, Daniele Apiletti, Elena Baralis

Proceedings of the International Workshop on Real-Time Business Intelligence and Analytics, 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

Proceedings of the 2019 IEEE International Congress on Big Data, 2019

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

Proceedings of the 2019 IEEE International Congress on Big Data, 2019

2018

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

Proceedings of the IEEE International Conference on Parallel & Distributed Processing with Applications, 2018

Useful ToPIC: Self-Tuning Strategies to Enhance Latent Dirichlet Allocation.

Stefano Proto, Evelina Di Corso, Francesco Ventura, Tania Cerquitelli

Proceedings of the 2018 IEEE International Congress on Big Data, 2018

Black-Box Model Explained Through an Assessment of Its Interpretable Features.

Francesco Ventura, Tania Cerquitelli, Francesco Giacalone

Proceedings of the New Trends in Databases and Information Systems, 2018

2017

Data miners' little helper: data transformation activity cues for cluster analysis on document collections.

Tania Cerquitelli, Evelina Di Corso, Francesco Ventura, Silvia Chiusano

Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, 2017

Prompting the data transformation activities for cluster analysis on collections of documents.

Tania Cerquitelli, Evelina Di Corso, Francesco Ventura, Silvia Chiusano

Proceedings of the 25th Italian Symposium on Advanced Database Systems, 2017

Self-tuning techniques for large scale cluster analysis on textual data collections.

Evelina Di Corso, Tania Cerquitelli, Francesco Ventura

Proceedings of the Symposium on Applied Computing, 2017

All in a twitter: Self-tuning strategies for a deeper understanding of a crisis tweet collection.

Evelina Di Corso, Francesco Ventura, Tania Cerquitelli

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017