In this paper, we focus on the design of Markov Chain Monte Carlo techniques in a statistical registration framework based on finite element basis (FE). Due to the use of FE basis...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
In this paper we propose the multirelational topic model (MRTM) for multiple types of link modeling such as citation and coauthor links in document networks. In the citation networ...
Jia Zeng, William K. Cheung, Chun-hung Li, Jiming ...
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...