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This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Diagnosability of systems is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. Generally, in the l...
Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicabil...
In recent years, the combinatorics of argumentation with arguments that can attack each other has been studied extensively. Especially, attack graphs (put in the focus of attentio...
In many applications of natural language processing (NLP) grammatically tagged corpora are needed. Thus Part of Speech (POS) Tagging is of high importance in the domain of NLP. Ma...
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
We propose an algorithm for segmentation of grayscale images. Our algorithm computes a solution to the convex, unconstrained minimization problem proposed by T. Chan, S. Esedo
Abstract. Principal component analysis (PCA) is a widely used technique for data analysis and dimensionality reduction. Eigenvalue decomposition is the standard algorithm for solvi...
This paper presents a new variant of Basic Particle Swarm Optimization (BPSO) algorithm named QI-PSO for solving global optimization problems. The QI-PSO algorithm makes use of a ...
: This paper presents a new approach to equalization of communication channels using Artificial Neural Networks (ANNs). A novel method of training the ANNs using Tabu based Back Pr...