We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
One of the major limitations of HMM-based models is the inability to cope with topology: When applied to a visible observation (VO) sequence, HMM-based techniques have difficulty ...
As more and more information is available in the Electronic Health Record in the form of free-text narrative, there is a need for automated tools, which can process and understand...
In this paper, we consider the relationship between risksensitivity and information. Product estimators are introduced as a generalization of Maximum A Posteriori Probability (MAP...
Vahid Reza Ramezani, Steven I. Marcus, Michael C. ...
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...