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ORCIDLuca Carminati
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2020 – today
- 2024
[j1]Luca Carminati, Federico Cacciamani:
Monte-Carlo Regret Minimization for Adversarial Team Games. Intelligenza Artificiale 18(2): 219-237 (2024)- [c6]Luca Carminati
, Fabiana Pirola, Alexandra Lagorio, Chiara Cimini, Arkadiusz Jurczuk, Xavier Boucher:
Skills, Technical and Organizational Support Needed for Collaborative Networks 5.0. PRO-VE (1) 2024: 380-396 - [c5]Mohammad Hossein Dehbozorgi, Monica Rossi, Sergio Terzi, Luca Carminati, Roberto Sala, Francesco Magni, Fabiana Pirola, Rossella Pozzi, Fernanda Strozzi, Tommaso Rossi:
AI Education for Tomorrow's Workforce: Leveraging Learning Factories for AI Education and Workforce Preparedness. RTSI 2024: 677-682 - [c4]Luca Carminati, Brian Hu Zhang, Gabriele Farina, Nicola Gatti, Tuomas Sandholm:
Hidden-Role Games: Equilibrium Concepts and Computation. EC 2024: 106-107 - 2023
- [i3]Luca Carminati, Brian Hu Zhang, Gabriele Farina, Nicola Gatti, Tuomas Sandholm:
Hidden-Role Games: Equilibrium Concepts and Computation. CoRR abs/2308.16017 (2023) - 2022
- [c3]Luca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti:
A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving. ICML 2022: 2638-2657 - [c2]Brian Hu Zhang, Luca Carminati, Federico Cacciamani, Gabriele Farina, Pierriccardo Olivieri, Nicola Gatti, Tuomas Sandholm:
Subgame Solving in Adversarial Team Games. NeurIPS 2022 - [i2]Luca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti:
Public Information Representation for Adversarial Team Games. CoRR abs/2201.10377 (2022) - [i1]Luca Carminati, Federico Cacciamani, Marco Ciccone, Nicola Gatti:
A Marriage between Adversarial Team Games and 2-player Games: Enabling Abstractions, No-regret Learning, and Subgame Solving. CoRR abs/2206.09161 (2022) - 2021
- [c1]Luca Carminati, Giacomo Lodigiani, Pietro Maldini, Samuele Meta, Stiven Metaj, Arcangelo Pisa, Alessandro Sanvito, Mattia Surricchio, Fernando Benjamín Pérez Maurera, Cesare Bernardis, Maurizio Ferrari Dacrema:
Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment. RecSys Challenge 2021: 28-33
Coauthor Index
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