— In this paper we use partially ordered sets (posets) to study decentralized control problems arising in different settings. We show that time delayed systems with certain dela...
This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polis...
Fluid flow in porous media is a dynamic process that is traditionally modeled using PDE (Partial Differential Equations). In this approach, physical properties related to fluid fl...
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...