Abstract: In this paper we present a novel method of using genetic algorithm (GA) to learn a graphical model which is used for human motion characterization. The modeling of human movements will ...

Suppose we observe samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and ...

We consider the problem of jointly estimating a collection of graphical models for discrete data, corresponding to several categories that share some common structure. An example for such a setting is ...

Abstract: Graphical models have been widely applied in distributed network computation problems such as inference in large-scale sensor networks. While belief propagation (BP) based on message passing ...

There are multiple ways to specify a graph. First, for an undirected graph, you can define it as a set of cliques. A clique is a subset of vertices of an undirected graph such that every two distinct ...

We propose a new probabilistic graphical model that jointly models the difficulties of questions, the abilities of participants and the correct answers to questions in aptitude testing and ...

A five-minute formula from Alexander Denev that takes you through a simple probabilistic graphical model and explains how and why these are used. Find out more about the ground-breaking book, ...