Parameter estimation is a key computational issue in all statistical image modeling techniques. In this paper, we explore a computationally efficient parameter estimation algorith...
We describe a hidden Markov modeling approach to multiple change-points that has attractive computational and statistical properties. This approach yields explicit recursive filter...
In this paper, a novel learning algorithm for Hidden Markov Models (HMMs) has been devised. The key issue is the achievement of a sparse model, i.e., a model in which all irreleva...
Background: Tiling arrays are an important tool for the study of transcriptional activity, proteinDNA interactions and chromatin structure on a genome-wide scale at high resolutio...
Parameter estimation of a continuous-time Markov chain observed through a discrete-time memoryless channel is studied. An expectation-maximization (EM) algorithm for maximum likeli...