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2020 – today
- 2024
[j7]Valentina Zangirolami
, Matteo Borrotti:
Dealing with uncertainty: Balancing exploration and exploitation in deep recurrent reinforcement learning. Knowl. Based Syst. 293: 111663 (2024)- 2023
- [i2]Valentina Zangirolami, Matteo Borrotti:
Impact of multi-armed bandit strategies on deep recurrent reinforcement learning. CoRR abs/2310.08331 (2023) - 2021
- [c5]Alessandro Riboni, Antonio Candelieri, Matteo Borrotti:
Deep Autonomous Agents Comparison for Self-driving Cars. LOD 2021: 201-213 - [i1]Alessandro Riboni, Nicolò Ghioldi, Antonio Candelieri, Matteo Borrotti:
Bayesian Optimization and Deep Learning forsteering wheel angle prediction. CoRR abs/2110.13629 (2021) - 2020
- [j6]Giorgio Lucarelli, Matteo Borrotti:
A deep Q-learning portfolio management framework for the cryptocurrency market. Neural Comput. Appl. 32(23): 17229-17244 (2020)
2010 – 2019
- 2019
- [c4]Giorgio Lucarelli, Matteo Borrotti:
A Deep Reinforcement Learning Approach for Automated Cryptocurrency Trading. AIAI 2019: 247-258 - 2017
- [j5]Matteo Borrotti, Francesco Sambo, Kalliopi Mylona, Steven G. Gilmour:
A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments. Stat. Comput. 27(2): 469-481 (2017) - 2016
- [j4]Matteo Borrotti, Giovanni Minervini, Davide De Lucrezia, Irene Poli:
Naïve Bayes ant colony optimization for designing high dimensional experiments. Appl. Soft Comput. 49: 259-268 (2016) - 2015
- [p1]Davide De March, Matteo Borrotti, Luca Sartore, Debora Slanzi, Lorenzo Podestà, Irene Poli:
A Predictive Approach Based on Neural Network Models for Building Automation Systems. Advances in Neural Networks 2015: 253-262 - 2014
- [j3]Matteo Borrotti, Davide De March, Debora Slanzi, Irene Poli:
Designing Lead Optimisation of MMP-12 Inhibitors. Comput. Math. Methods Medicine 2014: 258627:1-258627:8 (2014) - [j2]Francesco Sambo, Matteo Borrotti, Kalliopi Mylona:
A coordinate-exchange two-phase local search algorithm for the D- and I-optimal designs of split-plot experiments. Comput. Stat. Data Anal. 71: 1193-1207 (2014) - [j1]Davide Ferrari, Matteo Borrotti, Davide De March:
Response improvement in complex experiments by co-information composite likelihood optimization. Stat. Comput. 24(3): 351-363 (2014) - [c3]Debora Slanzi, Matteo Borrotti, Davide De March, Daniele Orlando, Silvio Giove, Irene Poli:
Qualitative Particle Swarm Optimization (Q-PSO) for Energy-Efficient Building Designs. WIVACE 2014: 13-25 - 2012
- [c2]Matteo Borrotti, Irene Poli:
Naïve Bayes Ant Colony Optimization for Experimental Design. SMPS 2012: 489-497 - 2010
- [c1]Matteo Borrotti, Davide De Lucrezia, Giovanni Minervini, Irene Poli:
A Model Based Ant Colony Design for the Protein Engineering Problem. ANTS Conference 2010: 352-359
Coauthor Index
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