Representation of multinomial linear hidden Markov models in the form of algebraic Bayesian networks

Introduction to Graphical Models, Hidden Markov Models and Bayesian Networks

heterogeneity within the orientalist discourse: representation of the orient in womens travelogues and mens paintings

from 1950s onward, new theories and critical approaches burgeoned across humanities. these theories were context-oriented; as a result, the analysis of discursive practices gained significance. thus, social, political, historical and cultural discourses that have been hitherto marginalized and considered inferior to literary texts, were introduced as important texts to be analyzed by critics. o...

Structural Bayesian Linear Regression for Hidden Markov Models

Linear regression for Hidden Markov Model (HMM) parameters is widely used for the adaptive training of time series pattern analysis especially for speech processing. The regression parameters are usually shared among sets of Gaussians in HMMs where the Gaussian clusters are represented by a tree. This paper realizes a fully Bayesian treatment of linear regression for HMMs considering this regre...

Consistency of Bayesian nonparametric Hidden Markov Models

We are interested in Bayesian nonparametric Hidden Markov Models. More precisely, we are going to prove the consistency of these models under appropriate conditions on the prior distribution and when the number of states of the Markov Chain is finite and known. Our approach is based on exponential forgetting and usual Bayesian consistency techniques.

Hidden Markov Models and Bayesian Networks for Counter-Terrorism

Introduction Information concerning the potential whereabouts and activities of terrorists can be extrapolated from the massive amount of intelligence reported daily to US intelligence agencies. The events encapsulated in these reports, and, in particular, the sequence of these events, can be used to probabilistically infer the activities of terrorists. In this chapter, we are particularly inte...