Matteo Borrotti

15 papers Misc 1Journal 9Unranked 4
YearRankTypeTitle / Venue / Authors
2024 J jnl
Dealing with uncertainty: Balancing exploration and exploitation in deep recurrent reinforcement learning.
Knowl. Based Syst.
Valentina Zangirolami, Matteo Borrotti
2023 J jnl
Impact of multi-armed bandit strategies on deep recurrent reinforcement learning.
CoRR
Valentina Zangirolami, Matteo Borrotti
2021 J jnl
Bayesian Optimization and Deep Learning forsteering wheel angle prediction.
CoRR
Alessandro Riboni, Nicolò Ghioldi, Antonio Candelieri, Matteo Borrotti
2021 — conf
Deep Autonomous Agents Comparison for Self-driving Cars.
LOD
Alessandro Riboni, Antonio Candelieri, Matteo Borrotti
2020 J jnl
A deep Q-learning portfolio management framework for the cryptocurrency market.
Neural Comput. Appl.
Giorgio Lucarelli, Matteo Borrotti
2019 Misc conf
A Deep Reinforcement Learning Approach for Automated Cryptocurrency Trading.
AIAI
Giorgio Lucarelli, Matteo Borrotti
2017 J jnl
A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments.
Stat. Comput.
Matteo Borrotti, Francesco Sambo, Kalliopi Mylona, Steven G. Gilmour
2016 J jnl
Naïve Bayes ant colony optimization for designing high dimensional experiments.
Appl. Soft Comput.
Matteo Borrotti, Giovanni Minervini, Davide De Lucrezia, Irene Poli
2015 — ch.
A Predictive Approach Based on Neural Network Models for Building Automation Systems.
Advances in Neural Networks
Davide De March, Matteo Borrotti, Luca Sartore, Debora Slanzi, Lorenzo Podestà, Irene Poli
2014 J jnl
A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments.
Comput. Stat. Data Anal.
Francesco Sambo, Matteo Borrotti, Kalliopi Mylona
2014 J jnl
Designing Lead Optimisation of MMP-12 Inhibitors.
Comput. Math. Methods Medicine
Matteo Borrotti, Davide De March, Debora Slanzi, Irene Poli
2014 — conf
Qualitative Particle Swarm Optimization (Q-PSO) for Energy-Efficient Building Designs.
WIVACE
Debora Slanzi, Matteo Borrotti, Davide De March, Daniele Orlando, Silvio Giove, Irene Poli
2014 J jnl
Response improvement in complex experiments by co-information composite likelihood optimization.
Stat. Comput.
Davide Ferrari, Matteo Borrotti, Davide De March
2012 — conf
Naïve Bayes Ant Colony Optimization for Experimental Design.
SMPS
Matteo Borrotti, Irene Poli
2010 — conf
A Model Based Ant Colony Design for the Protein Engineering Problem.
ANTS Conference
Matteo Borrotti, Davide De Lucrezia, Giovanni Minervini, Irene Poli