Evolutionary Computation

We develop formulae for updating parameters of sampling density functions via Geometric Algebra, Systems of ODE, Natural Gradients, Copulas, Bayesian Networks and Statistical Inference. Our current efforts aim to guide the parameter updating via modern strategies from Information Geometry, hence avoiding euclidean-space assumptions.

CIMAT - UTDallas

Ignacio Segovia-Dominguez
Ignacio Segovia-Dominguez
Visiting Scientist / Postdoctoral Research Associate

My research interests include topological and geometric methods in statistics and machine learning, analysis of complex dynamic networks, evolutionary computation, and computational statistics.