David Saltiel
According to our database1,
David Saltiel
authored at least 22 papers
between 2018 and 2024.
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Bibliography
2024
Optimizing Performance: How Compact Models Match or Exceed GPT's Classification Capabilities through Fine-Tuning.
CoRR, 2024
Examining Independence in Ensemble Sentiment Analysis: A Study on the Limits of Large Language Models Using the Condorcet Jury Theorem.
CoRR, 2024
Stress index strategy enhanced with financial news sentiment analysis for the equity markets.
CoRR, 2024
CoRR, 2024
2023
FSDA: Tackling Tail-Event Analysis in Imbalanced Time Series Data with Feature Selection and Data Augmentation.
Proceedings of the Fifth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2023
2022
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).
PhD thesis, 2022
2021
Adaptive learning for financial markets mixing model-based and model-free RL for volatility targeting.
CoRR, 2021
Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021
Explainable AI (XAI) Models Applied to the Multi-agent Environment of Financial Markets.
Proceedings of the Explainable and Transparent AI and Multi-Agent Systems, 2021
2020
CoRR, 2020
Proceedings of the Mining Data for Financial Applications - 5th ECML PKDD Workshop, 2020
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning.
Proceedings of the 25th International Conference on Pattern Recognition, 2020
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
Similarities between policy gradient methods in reinforcement and supervised learning.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020
2019
2018