Lorenzo Bisi

Orcid: 0000-0002-8688-5086

According to our database1, Lorenzo Bisi authored at least 13 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Exploiting Risk-Aversion and Size-dependent fees in FX Trading with Fitted Natural Actor-Critic.
CoRR, 2024

2023
Risk-averse optimization of reward-based coherent risk measures.
Artif. Intell., March, 2023

Simultaneously Updating All Persistence Values in Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Algorithms for risk-averse reinforcement learning.
PhD thesis, 2022

Risk-averse policy optimization via risk-neutral policy optimization.
Artif. Intell., 2022

Delayed Reinforcement Learning by Imitation.
Proceedings of the International Conference on Machine Learning, 2022

Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts.
Proceedings of the 3rd ACM International Conference on AI in Finance, 2022

Finite Sample Analysis of Mean-Volatility Actor-Critic for Risk-Averse Reinforcement Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Learning FX trading strategies with FQI and persistent actions.
Proceedings of the ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3, 2021

2020
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Control Frequency Adaptation via Action Persistence in Batch Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Foreign exchange trading: a risk-averse batch reinforcement learning approach.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

2017
Regret Minimization Algorithms for the Followers Behaviour Identification in Leadership Games.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017


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