Can Differential Evolution Be an Efficient Engine to Optimize Neural Networks? - Marco Baioletti; Gabriele Di Bari; Valentina Poggioni; Mirco Tracolli (MOD, 2017)

Evolutionary Algorithms with Neural Networks to optimize Big Data Cache. - Mirco Tracolli (DC@AI*IA, 2018)

An Intelligent Cache Management for Data Analysis at CMS. - Mirco Tracolli; Marco Baioletti; Diego Ciangottini; Valentina Poggioni; Daniele Spiga (ICCSA (2), 2020)

Effective Big Data Caching through Reinforcement Learning. - Mirco Tracolli; Marco Baioletti; Valentina Poggioni; Daniele Spiga (ICMLA, 2020)

Caching Suggestions Using Reinforcement Learning. - Mirco Tracolli; Marco Baioletti; Valentina Poggioni; Daniele Spiga (LOD (1), 2020)

Scattering with Programmable Matter. - Alfredo Navarra; Giuseppe Prencipe; Samuele Bonini; Mirco Tracolli (AINA (1), 2023)

Smart Caching in a Data Lake for High Energy Physics Analysis. - Tommaso Tedeschi; Marco Baioletti; Diego Ciangottini; Valentina Poggioni; Daniele Spiga; Loriano Storchi; Mirco Tracolli (J. Grid Comput., 2023)

Prototyping a ROOT-based distributed analysis workflow for HL-LHC: The CMS use case. - Tommaso Tedeschi; Vincenzo Eduardo Padulano; Daniele Spiga; Diego Ciangottini; Mirco Tracolli; Enric Tejedor Saavedra; Enrico Guiraud; Massimo Biasotto (Comput. Phys. Commun., 2024)