Feature selection with optimal coordinate ascent (OCA). - David Saltiel; Eric Benhamou (CoRR, 2018)

Trade Selection with Supervised Learning and OCA. - David Saltiel; Eric Benhamou (CoRR, 2018)

BCMA-ES: A Bayesian approach to CMA-ES. - Eric Benhamou; David Saltiel; Sébastien Vérel; Fabien Teytaud (CoRR, 2019)

BCMA-ES II: revisiting Bayesian CMA-ES. - Eric Benhamou; David Saltiel; Beatrice Guez; Nicolas Paris (CoRR, 2019)

NGO-GM: Natural Gradient Optimization for Graphical Models. - Eric Benhamou; Jamal Atif; Rida Laraki; David Saltiel (CoRR, 2019)

Similarities between policy gradient methods in reinforcement and supervised learning. - Eric Benhamou; David Saltiel (ESANN, 2020)

Bayesian CMA-ES: a new approach. - Eric Benhamou; David Saltiel; Sébastien Vérel (GECCO Companion, 2020)

Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning. - Eric Benhamou; David Saltiel; Jean-Jacques Ohana; Jamal Atif (ICPR, 2020)

Deep Reinforcement Learning (DRL) for Portfolio Allocation. - Eric Benhamou; David Saltiel; Jean-Jacques Ohana; Jamal Atif; Rida Laraki (ECML/PKDD (5), 2020)

Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA). - David Saltiel; Eric Benhamou; Rida Laraki; Jamal Atif (MIDAS@PKDD/ECML, 2020)

Time your hedge with Deep Reinforcement Learning. - Eric Benhamou; David Saltiel; Sandrine Ungari; Abhishek Mukhopadhyay (CoRR, 2020)

AAMDRL: Augmented Asset Management with Deep Reinforcement Learning. - Eric Benhamou; David Saltiel; Sandrine Ungari; Abhishek Mukhopadhyay; Jamal Atif (CoRR, 2020)

Bridging the gap between Markowitz planning and deep reinforcement learning. - Eric Benhamou; David Saltiel; Sandrine Ungari; Abhishek Mukhopadhyay (CoRR, 2020)

Explainable AI (XAI) Models Applied to the Multi-agent Environment of Financial Markets. - Jean-Jacques Ohana; Steve Ohana; Eric Benhamou; David Saltiel; Beatrice Guez (EXTRAAMAS@AAMAS, 2021)

Adaptive Supervised Learning for Financial Markets Volatility Targeting Models. - Eric Benhamou; David Saltiel; Serge Tabachnik; Corentin Bourdeix; François Chareyron; Beatrice Guez (PKDD/ECML Workshops (2), 2021)

Adaptive learning for financial markets mixing model-based and model-free RL for volatility targeting. - Eric Benhamou; David Saltiel; Serge Tabachnik; Sui Kai Wong; François Chareyron (CoRR, 2021)

Model-based versus model-free reinforcement learning in quantitative asset management. (Apprentissage par renforcement basé sur un modèle ou sans modèle dans la gestion quantitative des actifs). - David Saltiel (2022)

FSDA: Tackling Tail-Event Analysis in Imbalanced Time Series Data with Feature Selection and Data Augmentation. - Raphael Krief; Eric Benhamou; Beatrice Guez; Jean-Jacques Ohana; David Saltiel; Rida Laraki; Jamal Atif (LIDTA, 2023)

Comparing Deep RL and Traditional Financial Portfolio Methods. - Eric Benhamou; Jean-Jacques Ohana; Beatrice Guez; David Saltiel; Rida Laraki; Jamal Atif (PKDD/ECML Workshops (5), 2023)

Sentiment Score of Bloomberg Market Wraps with ChatGPT. - Baptiste Lefort; Eric Benhamou; Jean-Jacques Ohana; Beatrice Guez; David Saltiel (ICDM (Workshops), 2024)

Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? - Baptiste Lefort; Eric Benhamou; Jean-Jacques Ohana; David Saltiel; Beatrice Guez; Damien Challet (CoRR, 2024)

Stress index strategy enhanced with financial news sentiment analysis for the equity markets. - Baptiste Lefort; Eric Benhamou; Jean-Jacques Ohana; David Saltiel; Beatrice Guez; Thomas Jacquot (CoRR, 2024)

Examining Independence in Ensemble Sentiment Analysis: A Study on the Limits of Large Language Models Using the Condorcet Jury Theorem. - Baptiste Lefort; Eric Benhamou; Jean-Jacques Ohana; Beatrice Guez; David Saltiel; Thomas Jacquot (CoRR, 2024)

Optimizing Performance: How Compact Models Match or Exceed GPT's Classification Capabilities through Fine-Tuning. - Baptiste Lefort; Eric Benhamou; Jean-Jacques Ohana; David Saltiel; Beatrice Guez (CoRR, 2024)