Mirko Polato - researchr alias

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 43 from 43

2025

Improving rule-based classifiers by Bayes point aggregationLuca Bergamin, Mirko Polato, Fabio Aiolli. ijon, 613:128699, 2025. [doi]

2024

A Survey on Hypergraph Representation LearningAlessia Antelmi, Gennaro Cordasco, Mirko Polato, Vittorio Scarano, Carmine Spagnuolo, Dingqi Yang. ACM Comput. Surv., 56(1), January 2024. [doi]

A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step GuideSunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin. kdd 2024: 6534-6544 [doi]

2023

2022

On the feasibility of crawling-based attacks against recommender systemsFabio Aiolli, Mauro Conti, Stjepan Picek, Mirko Polato. jcs, 30(4):599-621, 2022. [doi]

Novel Applications for VAE-based Anomaly Detection SystemsLuca Bergamin, Tommaso Carraro, Mirko Polato, Fabio Aiolli. ijcnn 2022: 1-8 [doi]

Conditioned Variational Autoencoder for Top-N Item RecommendationTommaso Carraro, Mirko Polato, Luca Bergamin, Fabio Aiolli. icann 2022: 785-796 [doi]

Dissociation Between Users' Explicit and Implicit Attitudes Toward Artificial Intelligence: An Experimental StudyValentina Fietta, Francesca Zecchinato, Brigida Di Stasi, Mirko Polato, Merylin Monaro. thms, 52(3):481-489, 2022. [doi]

Bayes Point Rule Set LearningMirko Polato, Fabio Aiolli, Luca Bergamin, Tommaso Carraro. esann 2022: [doi]

Boosting the Federation: Cross-Silo Federated Learning without Gradient DescentMirko Polato, Roberto Esposito, Marco Aldinucci. ijcnn 2022: 1-10 [doi]

PRL: A game theoretic large margin method for interpretable feature learningMirko Polato, Guglielmo Faggioli, Fabio Aiolli. ijon, 479:106-120, 2022. [doi]

2021

Propositional KernelsMirko Polato, Fabio Aiolli. entropy, 23(8):1020, 2021. [doi]

Efficient Multilingual Deep Learning Model for Keyword CategorizationMirko Polato, Denys Demchenko, Almat Kuanyshkereyev, Nicolò Navarin. ssci 2021: 1-8 [doi]

Privacy-Preserving Kernel Computation For Vertically Partitioned DataMirko Polato, Alberto Gallinaro, Fabio Aiolli. esann 2021: [doi]

2020

2019

Mind your wallet's privacy: identifying Bitcoin wallet apps and user's actions through network traffic analysisFabio Aiolli, Mauro Conti, Ankit Gangwal, Mirko Polato. SAC 2019: 1484-1491 [doi]

Evaluation of Tag Clusterings for User Profiling in Movie RecommendationGuglielmo Faggioli, Mirko Polato, Ivano Lauriola, Fabio Aiolli. icann 2019: 456-468 [doi]

Tag-Based User Profiling: A Game Theoretic ApproachGuglielmo Faggioli, Mirko Polato, Fabio Aiolli. um 2019: 267-271 [doi]

A Preference-Learning Framework for Modeling Relational DataIvano Lauriola, Mirko Polato, Guglielmo Faggioli, Fabio Aiolli. inns 2020: 359-369 [doi]

Boolean kernels for rule based interpretation of support vector machinesMirko Polato, Fabio Aiolli. ijon, 342:113-124, 2019. [doi]

Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule LearningMirko Polato, Fabio Aiolli. AAAI 2019: 4723-4730 [doi]

Playing the Large Margin Preference GameMirko Polato, Guglielmo Faggioli, Ivano Lauriola, Fabio Aiolli. icann 2019: 792-804 [doi]

2018

Efficient Similarity Based Methods For The Playlist Continuation TaskGuglielmo Faggioli, Mirko Polato, Fabio Aiolli. recsys 2018: [doi]

The minimum effort maximum output principle applied to Multiple Kernel LearningIvano Lauriola, Mirko Polato, Fabio Aiolli. esann 2018: [doi]

Learning Preferences for Large Scale Multi-label ProblemsIvano Lauriola, Mirko Polato, Alberto Lavelli, Fabio Rinaldi 0001, Fabio Aiolli. icann 2018: 546-555 [doi]

Boolean kernels for collaborative filtering in top-N item recommendationMirko Polato, Fabio Aiolli. ijon, 286:214-225, 2018. [doi]

A Novel Boolean Kernels Family for Categorical DataMirko Polato, Ivano Lauriola, Fabio Aiolli. entropy, 20(6):444, 2018. [doi]

A Game-Theoretic Framework for Interpretable Preference and Feature LearningMirko Polato, Fabio Aiolli. icann 2018: 659-668 [doi]

Boolean kernels for interpretable kernel machinesMirko Polato, Fabio Aiolli. esann 2018: [doi]

Time and activity sequence prediction of business process instancesMirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni. computing, 100(9):1005-1031, 2018. [doi]

2017

2016

Kernel based collaborative filtering for very large scale top-N item recommendationFabio Aiolli, Mirko Polato. esann 2016: [doi]

A preliminary study on a recommender system for the job recommendation challengeMirko Polato, Fabio Aiolli. recsys 2016: [doi]

2014

Data-aware remaining time prediction of business process instancesMirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni. ijcnn 2014: 816-823 [doi]

See Also

All Publications

Filter by Year
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Tag

Filter by Venue

[+]
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1

Researchr

Publications by 'Mirko Polato'

Viewing Publication 1 - 43 from 43

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2014

See Also

All Publications

Filter by YearOR AND NOT 1

Filter by TypeOR AND NOT 1

Filter by Tag

Filter by Venue [+]OR AND NOT 1

Filter by Author [+]OR AND NOT 1

Filter by Top Terms [+]OR AND NOT 1

Researchr

Publications by 'Mirko Polato'

Viewing Publication 1 - 43 from 43

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2014

Filter by Year
OR AND NOT 1

Filter by Type
OR AND NOT 1

Filter by Venue

[+]
OR AND NOT 1

Filter by Author

[+]
OR AND NOT 1

Filter by Top Terms

[+]
OR AND NOT 1