2 citations · 2 across the 3 of their papers we have counts for
12 papers · 1 filter
Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets
Eric Benhamou
In this paper, we revisit the Kalman filter theory. After giving the intuition on a simplified financial markets example, we revisit the maths underlying it. We then show that Kalm…
Trade Selection with Supervised Learning and OCA
David Saltiel, Eric Benhamou
In recent years, state-of-the-art methods for supervised learning have exploited increasingly gradient boosting techniques, with mainstream efficient implementations such as xgboos…
Feature selection with optimal coordinate ascent (OCA)
David Saltiel, Eric Benhamou
In machine learning, Feature Selection (FS) is a major part of efficient algorithm. It fuels the algorithm and is the starting block for our prediction. In this paper, we present a…
A discrete version of CMA-ES
Eric Benhamou, Jamal Atif, Rida Laraki
Modern machine learning uses more and more advanced optimization techniques to find optimal hyper parameters. Whenever the objective function is non-convex, non continuous and with…
A new approach to learning in Dynamic Bayesian Networks (DBNs)
E. Benhamou, J. Atif, R. Laraki
In this paper, we revisit the parameter learning problem, namely the estimation of model parameters for Dynamic Bayesian Networks (DBNs). DBNs are directed graphical models of stoc…
Three remarkable properties of the Normal distribution
Eric Benhamou, Beatrice Guez, Nicolas Paris
In this paper, we present three remarkable properties of the normal distribution: first that if two independent variables's sum is normally distributed, then each random variable f…