We propose a novel nonparametric Bayesian model, Dual Hierarchical Dirichlet Processes (Dual-HDP), for trajectory analysis and semantic region modeling in surveillance settings, i...
Xiaogang Wang, Keng Teck Ma, Gee Wah Ng, W. Eric L...
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
We present an analysis of user conversations in on-line social media and their evolution over time. We propose a dynamic model that predicts the growth dynamics and structural pro...
The importance of metadata has been broadly referred in the last years, mainly in the field of data warehousing and decision support systems. Contemporarily, in the adjacent field...