We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Background: Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservati...
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...