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Eric Benhamou
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Books and Theses
- 2023
- [b1]Eric Benhamou:
Mathematical study of Peierls instability in the discrete polyacetylene model. (Étude mathématique de l'instabilité de Peierls dans le modèle discret du polyacétylène). PSL University, Paris, France, 2023
Journal Articles
- 2010
- [j4]Eric Benhamou, Jon Eisenberg
, Randy H. Katz:
Assessing the changing U.S. IT R&D ecosystem. Commun. ACM 53(2): 76-83 (2010) - [j3]Eric Benhamou, Emmanuel Gobet, Mohammed Miri:
Time Dependent Heston Model. SIAM J. Financial Math. 1(1): 289-325 (2010) - 2009
- [j2]Eric Benhamou, Emmanuel Gobet, Mohammed Miri:
Smart expansion and fast calibration for jump diffusions. Finance Stochastics 13(4): 563-589 (2009) - 1983
- [j1]Eric Benhamou, Judy Estrin:
Multilevel Internetworking Gateways: Architecture and Applications. Computer 16(9): 27-34 (1983)
Conference and Workshop Papers
- 2023
- [c11]Raphael Krief, Eric Benhamou, Beatrice Guez, Jean-Jacques Ohana, David Saltiel, Rida Laraki, Jamal Atif:
FSDA: Tackling Tail-Event Analysis in Imbalanced Time Series Data with Feature Selection and Data Augmentation. LIDTA 2023: 45-58 - 2021
- [c10]Jean-Jacques Ohana, Steve Ohana, Eric Benhamou, David Saltiel, Beatrice Guez:
Explainable AI (XAI) Models Applied to the Multi-agent Environment of Financial Markets. EXTRAAMAS@AAMAS 2021: 189-207 - [c9]Eric Benhamou, David Saltiel, Serge Tabachnik, Corentin Bourdeix, François Chareyron, Beatrice Guez:
Adaptive Supervised Learning for Financial Markets Volatility Targeting Models. PKDD/ECML Workshops (2) 2021: 195-209 - 2020
- [c8]Céline Beji, Eric Benhamou, Michaël Bon, Florian Yger, Jamal Atif:
Estimating Individual Treatment Effects through Causal Populations Identification. ESANN 2020: 43-48 - [c7]Eric Benhamou, David Saltiel:
Similarities between policy gradient methods in reinforcement and supervised learning. ESANN 2020: 721-726 - [c6]Eric Benhamou, David Saltiel, Sébastien Vérel
:
Bayesian CMA-ES: a new approach. GECCO Companion 2020: 203-204 - [c5]Eric Benhamou, David Saltiel, Jean-Jacques Ohana, Jamal Atif:
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning. ICPR 2020: 10050-10057 - [c4]David Saltiel, Eric Benhamou, Rida Laraki, Jamal Atif:
Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA). MIDAS@PKDD/ECML 2020: 1-15 - [c3]Eric Benhamou, David Saltiel, Jean-Jacques Ohana, Jamal Atif, Rida Laraki:
Deep Reinforcement Learning (DRL) for Portfolio Allocation. ECML/PKDD (5) 2020: 527-531 - 2000
- [c2]Eric Benhamou, Thomas Serval:
On the Competition between ECNs, Stock Markets and Market Makers. EC-Web 2000: 291-300 - 1984
- [c1]Valerie Lasker, Monte Lien, Eric Benhamou:
An Architecture for high Performance Protocol Implementation. INFOCOM 1984: 156-164
Informal and Other Publications
- 2024
- [i17]Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana, David Saltiel, Beatrice Guez, Damien Challet:
Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps? CoRR abs/2401.05447 (2024) - [i16]Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana, David Saltiel, Beatrice Guez, Thomas Jacquot:
Stress index strategy enhanced with financial news sentiment analysis for the equity markets. CoRR abs/2404.00012 (2024) - 2021
- [i15]Eric Benhamou, David Saltiel, Serge Tabachnik, Sui Kai Wong, François Chareyron:
Adaptive learning for financial markets mixing model-based and model-free RL for volatility targeting. CoRR abs/2104.10483 (2021) - 2020
- [i14]Eric Benhamou
, David Saltiel, Jean-Jacques Ohana, Jamal Atif:
Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning. CoRR abs/2009.07200 (2020) - [i13]Eric Benhamou
, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay:
Time your hedge with Deep Reinforcement Learning. CoRR abs/2009.14136 (2020) - [i12]Eric Benhamou
, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay, Jamal Atif:
AAMDRL: Augmented Asset Management with Deep Reinforcement Learning. CoRR abs/2010.08497 (2020) - [i11]Eric Benhamou
, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay:
Bridging the gap between Markowitz planning and deep reinforcement learning. CoRR abs/2010.09108 (2020) - 2019
- [i10]Eric Benhamou
, David Saltiel, Sébastien Vérel, Fabien Teytaud:
BCMA-ES: A Bayesian approach to CMA-ES. CoRR abs/1904.01401 (2019) - [i9]Eric Benhamou
, David Saltiel, Beatrice Guez, Nicolas Paris:
BCMA-ES II: revisiting Bayesian CMA-ES. CoRR abs/1904.01466 (2019) - [i8]Eric Benhamou
:
Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL). CoRR abs/1904.06260 (2019) - [i7]Eric Benhamou
, Jamal Atif, Rida Laraki, David Saltiel:
NGO-GM: Natural Gradient Optimization for Graphical Models. CoRR abs/1905.05444 (2019) - [i6]Eric Benhamou
:
Variance Reduction in Actor Critic Methods (ACM). CoRR abs/1907.09765 (2019) - 2018
- [i5]Eric Benhamou:
Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets. CoRR abs/1811.11618 (2018) - [i4]David Saltiel, Eric Benhamou
:
Feature selection with optimal coordinate ascent (OCA). CoRR abs/1811.12064 (2018) - [i3]David Saltiel, Eric Benhamou
:
Trade Selection with Supervised Learning and OCA. CoRR abs/1812.04486 (2018) - [i2]Eric Benhamou, Jamal Atif, Rida Laraki, Anne Auger:
A new approach to learning in Dynamic Bayesian Networks (DBNs). CoRR abs/1812.09027 (2018) - [i1]Eric Benhamou
, Jamal Atif, Rida Laraki, Anne Auger:
A discrete version of CMA-ES. CoRR abs/1812.11859 (2018)
Coauthor Index
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
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