2 papers
q-fin.PM2025
Regret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards
Daniil Karzanov, Rubén Garzón, Mikhail Terekhov +3
This paper introduces a novel agent-based approach for enhancing existing portfolio strategies using Proximal Policy Optimization (PPO). Rather than focusing solely on traditional…
cs.LG2024
Post-processing fairness with minimal changes
Federico Di Gennaro, Thibault Laugel, Vincent Grari +2
In this paper, we introduce a novel post-processing algorithm that is both model-agnostic and does not require the sensitive attribute at test time. In addition, our algorithm is e…