Mirko Polato - RankMe

66 papers A* 2A 3B 12Misc 1Journal 27Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fluke: Federated learning utility framework for experimentation and research. Future Gener. Comput. Syst. Mirko Polato
2026	J	`jnl`	Learning in federated and dynamic environments: A tutorial on challenges, trends, and practical strategies. Neurocomputing Mirko Polato, Barbara Hammer, Manuel Röder, Frank-Michael Schleif
2026	—	`ed.`	Proceedings of the 4th Italian Conference on Big Data and Data Science (ITADATA 2025), Turin, Italy, September 9-11, 2025 ITADATA Nicola Bena, Michelangelo Ceci, Roberto Esposito, Riccardo Torlone, Alex Della Bruna, Claudio A. Ardagna, Mirko Polato, Luigi Romano
2025	A	`conf`	A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. CIKM Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2025	A	`conf`	Fed2RC: Federated Rocket Kernels and Ridge Classifier for Time Series Classification. ECAI Bruno Casella, Samuele Fonio, Lorenzo Sciandra, Claudio Gallicchio, Marco Aldinucci, Mirko Polato, Roberto Esposito
2025	—	`conf`	Hypergraph Motif Representation Learning. KDD (1) Alessia Antelmi, Gennaro Cordasco, Daniele De Vinco, Valerio Di Pasquale, Mirko Polato, Carmine Spagnuolo
2025	J	`jnl`	Improving rule-based classifiers by Bayes point aggregation. Neurocomputing Luca Bergamin, Mirko Polato, Fabio Aiolli
2025	J	`jnl`	PriVeriFL: Privacy-Preserving and Aggregation-Verifiable Federated Learning. IEEE Trans. Serv. Comput. Lulu Wang, Mirko Polato, Alessandro Brighente, Mauro Conti, Lei Zhang, Lin Xu
2025	J	`jnl`	SVF: Support Vector Federation. IEEE Access Mirko Polato, Roberto Esposito, Lorenzo Sciandra
2024	A*	`conf`	A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. KDD Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2024	J	`jnl`	A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. CoRR Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin
2024	J	`jnl`	A Survey on Hypergraph Representation Learning. ACM Comput. Surv. Alessia Antelmi, Gennaro Cordasco, Mirko Polato, Vittorio Scarano, Carmine Spagnuolo, Dingqi Yang
2024	B	`conf`	FedHP: Federated Learning with Hyperspherical Prototypical Regularization. ESANN Samuele Fonio, Mirko Polato, Roberto Esposito
2024	B	`conf`	Machine learning in distributed, federated and non-stationary environments - recent trends. ESANN Mirko Polato, Barbara Hammer, Frank-Michael Schleif
2024	B	`conf`	Vision Language Models as Policy Learners in Reinforcement Learning Environments. ESANN Giovanni Bonetta, Davide Zago, Rossella Cancelliere, Mirko Polato, Bernardo Magnini
2024	J	`jnl`	fluke: Federated Learning Utility frameworK for Experimentation and research. CoRR Mirko Polato
2023	—	`conf`	1st Workshop on Federated Learning Technologies. WWW (Companion Volume) Mirko Polato, Roberto Esposito, Walter Riviera, Zenglin Xu, Irwin King
2023	—	`conf`	Boosting Methods for Federated Learning. SEBD Roberto Esposito, Mirko Polato, Marco Aldinucci
2023	J	`jnl`	Experimenting with Emerging ARM and RISC-V Systems for Decentralised Machine Learning. CoRR Gianluca Mittone, Nicolò Tonci, Robert Birke, Iacopo Colonnelli, Doriana Medic, Andrea Bartolini, Roberto Esposito, Emanuele Parisi, Francesco Beneventi, Mirko Polato, Massimo Torquati, Luca Benini, Marco Aldinucci
2023	—	`conf`	Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning. CF Gianluca Mittone, Nicolò Tonci, Robert Birke, Iacopo Colonnelli, Doriana Medic, Andrea Bartolini, Roberto Esposito, Emanuele Parisi, Francesco Beneventi, Mirko Polato, Massimo Torquati, Luca Benini, Marco Aldinucci
2022	B	`conf`	Bayes Point Rule Set Learning. ESANN Mirko Polato, Fabio Aiolli, Luca Bergamin, Tommaso Carraro
2022	J	`jnl`	Bayes Point Rule Set Learning. CoRR Fabio Aiolli, Luca Bergamin, Tommaso Carraro, Mirko Polato
2022	B	`conf`	Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent. IJCNN Mirko Polato, Roberto Esposito, Marco Aldinucci
2022	—	`conf`	Conditioned Variational Autoencoder for Top-N Item Recommendation. ICANN (2) Tommaso Carraro, Mirko Polato, Luca Bergamin, Fabio Aiolli
2022	J	`jnl`	Dissociation Between Users' Explicit and Implicit Attitudes Toward Artificial Intelligence: An Experimental Study. IEEE Trans. Hum. Mach. Syst. Valentina Fietta, Francesca Zecchinato, Brigida Di Stasi, Mirko Polato, Merylin Monaro
2022	B	`conf`	Novel Applications for VAE-based Anomaly Detection Systems. IJCNN Luca Bergamin, Tommaso Carraro, Mirko Polato, Fabio Aiolli
2022	J	`jnl`	Novel Applications for VAE-based Anomaly Detection Systems. CoRR Luca Bergamin, Tommaso Carraro, Mirko Polato, Fabio Aiolli
2022	J	`jnl`	On the feasibility of crawling-based attacks against recommender systems. J. Comput. Secur. Fabio Aiolli, Mauro Conti, Stjepan Picek, Mirko Polato
2022	J	`jnl`	PRL: A game theoretic large margin method for interpretable feature learning. Neurocomputing Mirko Polato, Guglielmo Faggioli, Fabio Aiolli
2021	—	`conf`	Efficient Multilingual Deep Learning Model for Keyword Categorization. SSCI Mirko Polato, Denys Demchenko, Almat Kuanyshkereyev, Nicolò Navarin
2021	B	`conf`	Federated Variational Autoencoder for Collaborative Filtering. IJCNN Mirko Polato
2021	B	`conf`	Privacy-Preserving Kernel Computation For Vertically Partitioned Data. ESANN Mirko Polato, Alberto Gallinaro, Fabio Aiolli
2021	J	`jnl`	Propositional Kernels. Entropy Mirko Polato, Fabio Aiolli
2020	—	`conf`	A Look Inside the Black-Box: Towards the Interpretability of Conditioned Variational Autoencoder for Collaborative Filtering. UMAP (Adjunct Publication) Tommaso Carraro, Mirko Polato, Fabio Aiolli
2020	—	`conf`	Big Enough to Care Not Enough to Scare! Crawling to Attack Recommender Systems. ESORICS (2) Fabio Aiolli, Mauro Conti, Stjepan Picek, Mirko Polato
2020	J	`jnl`	Conditioned Variational Autoencoder for top-N item recommendation. CoRR Mirko Polato, Tommaso Carraro, Fabio Aiolli
2020	J	`jnl`	Learning deep kernels in the space of monotone conjunctive polynomials. Pattern Recognit. Lett. Ivano Lauriola, Mirko Polato, Fabio Aiolli
2020	A	`conf`	Recency Aware Collaborative Filtering for Next Basket Recommendation. UMAP Guglielmo Faggioli, Mirko Polato, Fabio Aiolli
2019	—	`conf`	A Preference-Learning Framework for Modeling Relational Data. INNSBDDL Ivano Lauriola, Mirko Polato, Guglielmo Faggioli, Fabio Aiolli
2019	J	`jnl`	Boolean kernels for rule based interpretation of support vector machines. Neurocomputing Mirko Polato, Fabio Aiolli
2019	—	`conf`	Evaluation of Tag Clusterings for User Profiling in Movie Recommendation. ICANN (Workshop) Guglielmo Faggioli, Mirko Polato, Ivano Lauriola, Fabio Aiolli
2019	A*	`conf`	Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning. AAAI Mirko Polato, Fabio Aiolli
2019	Misc	`conf`	Mind your wallet's privacy: identifying Bitcoin wallet apps and user's actions through network traffic analysis. SAC Fabio Aiolli, Mauro Conti, Ankit Gangwal, Mirko Polato
2019	—	`conf`	Playing the Large Margin Preference Game. ICANN (2) Mirko Polato, Guglielmo Faggioli, Ivano Lauriola, Fabio Aiolli
2019	—	`conf`	Tag-Based User Profiling: A Game Theoretic Approach. UMAP (Adjunct Publication) Guglielmo Faggioli, Mirko Polato, Fabio Aiolli
2018	—	`conf`	A Game-Theoretic Framework for Interpretable Preference and Feature Learning. ICANN (1) Mirko Polato, Fabio Aiolli
2018	J	`jnl`	A Novel Boolean Kernels Family for Categorical Data. Entropy Mirko Polato, Ivano Lauriola, Fabio Aiolli
2018	J	`jnl`	Boolean kernels for collaborative filtering in top-N item recommendation. Neurocomputing Mirko Polato, Fabio Aiolli
2018	B	`conf`	Boolean kernels for interpretable kernel machines. ESANN Mirko Polato, Fabio Aiolli
2018	—	`conf`	Efficient Similarity Based Methods For The Playlist Continuation Task. RecSys Challenge Guglielmo Faggioli, Mirko Polato, Fabio Aiolli
2018	J	`jnl`	Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning. CoRR Mirko Polato, Fabio Aiolli
2018	—	`conf`	Learning Preferences for Large Scale Multi-label Problems. ICANN (1) Ivano Lauriola, Mirko Polato, Alberto Lavelli, Fabio Rinaldi, Fabio Aiolli
2018	B	`conf`	The minimum effort maximum output principle applied to Multiple Kernel Learning. ESANN Ivano Lauriola, Mirko Polato, Fabio Aiolli
2018	J	`jnl`	Time and activity sequence prediction of business process instances. Computing Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni
2017	—	`conf`	Classification of Categorical Data in the Feature Space of Monotone DNFs. ICANN (2) Mirko Polato, Ivano Lauriola, Fabio Aiolli
2017	—	`conf`	Disjunctive Boolean Kernels-based Collaborative Filtering for top-N Item Recommendation. IIR Mirko Polato, Fabio Aiolli
2017	J	`jnl`	Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation. Neurocomputing Mirko Polato, Fabio Aiolli
2017	J	`jnl`	LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instances. CoRR Nicolò Navarin, Beatrice Vincenzi, Mirko Polato, Alessandro Sperduti
2017	—	`conf`	LSTM networks for data-aware remaining time prediction of business process instances. SSCI Nicolò Navarin, Beatrice Vincenzi, Mirko Polato, Alessandro Sperduti
2017	—	`conf`	Radius-Margin Ratio Optimization for Dot-Product Boolean Kernel Learning. ICANN (2) Ivano Lauriola, Mirko Polato, Fabio Aiolli
2016	—	`conf`	A preliminary study on a recommender system for the job recommendation challenge. RecSys Challenge Mirko Polato, Fabio Aiolli
2016	J	`jnl`	Disjunctive Boolean Kernels for Collaborative Filtering in Top-N Recommendation. CoRR Mirko Polato, Fabio Aiolli
2016	J	`jnl`	Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation. CoRR Mirko Polato, Fabio Aiolli
2016	B	`conf`	Kernel based collaborative filtering for very large scale top-N item recommendation. ESANN Fabio Aiolli, Mirko Polato
2016	J	`jnl`	Time and Activity Sequence Prediction of Business Process Instances. CoRR Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni
2014	B	`conf`	Data-aware remaining time prediction of business process instances. IJCNN Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni