Search Results - "Polato, Mirko"

A survey on multimodal federated learning.

Authors: Grosso, Silvia Benarba, Nawel Bouchenak, Sara et al.

Source: Neural Computing & Applications; Jun2026, Vol. 38 Issue 11, p1-33, 33p

On the feasibility of crawling-based attacks against recommender systems1.

Authors: Aiolli, Fabio Conti, Mauro Picek, Stjepan et al.

Source: Journal of Computer Security; 2022, Vol. 30 Issue 4, p599-621, 23p

Learning in federated and dynamic environments: A tutorial on challenges, trends, and practical strategies.

Authors: Polato, Mirko Hammer, Barbara Röder, Manuel et al.

Source: Neurocomputing; Apr2026, Vol. 672, pN.PAG-N.PAG, 1p

Fluke: Federated learning utility framework for experimentation and research.

Authors: Polato, Mirko¹, mirko.polato@unito.it

Source: Future Generation Computer Systems; Apr2026, Vol. 177, pN.PAG-N.PAG, 1p

PRL: A game theoretic large margin method for interpretable feature learning.

Authors: Polato, Mirko Faggioli, Guglielmo Aiolli, Fabio

Source: Neurocomputing; Mar2022, Vol. 479, p106-120, 15p

Learning deep kernels in the space of monotone conjunctive polynomials.

Authors: Lauriola, Ivano Polato, Mirko Aiolli, Fabio

Source: Pattern Recognition Letters; Dec2020, Vol. 140, p200-206, 7p

Time and activity sequence prediction of business process instances.

Authors: Polato, Mirko Sperduti, Alessandro Burattin, Andrea et al.

Source: Computing; Sep2018, Vol. 100 Issue 9, p1005-1031, 27p

Improving rule-based classifiers by Bayes point aggregation.

Authors: Bergamin, Luca Polato, Mirko Aiolli, Fabio

Source: Neurocomputing; Jan2025, Vol. 613, pN.PAG-N.PAG, 1p

Boolean kernels for rule based interpretation of support vector machines.

Authors: Polato, Mirko Aiolli, Fabio

Source: Neurocomputing; May2019, Vol. 342, p113-124, 12p

A Survey on Hypergraph Representation Learning.

Authors: ANTELMI, ALESSIA CORDASCO, GENNARO POLATO, MIRKO et al.

Source: ACM Computing Surveys. Jan2024, Vol. 56 Issue 1, p1-38. 38p.

Social Support and Help-Seeking Among Suicide Bereaved: A Study With Italian Survivors.

Authors: Entilli, Lorenza Leo, Diego De Aiolli, Fabio et al.

Source: Omega: Journal of Death & Dying. Jun2023, Vol. 87 Issue 2, p534-553. 20p. 5 Charts.

Subject Terms: *Help-seeking behavior, Suicide, Expert systems, Well-being, Social support, Cross-sectional method, Internet, Satisfaction, Psychologists, Suicidal ideation, Surveys, Sex discrimination, Research funding, Bereavement

Geographic Terms: Italy

Propositional Kernels.

Authors: Polato, Mirko Aiolli, Fabio

Source: Entropy. Aug2021, Vol. 23 Issue 8, p1020. 1p.

On the feasibility of crawling-based attacks against recommender systems¹.

Authors: Aiolli, Fabio Conti, Mauro Picek, Stjepan et al.

Source: Journal of Computer Security. 2022, Vol. 30 Issue 4, p599-621. 23p.

On the feasibility of crawling-based attacks against recommender systems¹.

Authors: Aiolli, Fabio Conti, Mauro Picek, Stjepan et al.

Source: Journal of Computer Security. 2022, Vol. 30 Issue 4, p599-621. 23p.

Subjects: Recommender systems, Internet access, User experience

A Novel Boolean Kernels Family for Categorical Data †.

Authors: Polato, Mirko Lauriola, Ivano Aiolli, Fabio

Source: Entropy. Jun2018, Vol. 20 Issue 6, p444. 1p.

Text-Aware Predictive Monitoring of Business Processes.

Authors: Pegoraro, Marco Uysal, Merih Seran Georgi, David Benedikt et al.

Source: Business Information Systems (2747-9986). 2021, p221-232. 12p.