We present a complete system for the purpose of automatically assembling 3D pots given 3D measurements of their fragments commonly called sherds. A Bayesian approach is formulated...
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
In real world, an image is usually associated with multiple labels which are characterized by different regions in the image. Thus image classification is naturally posed as both ...
Zheng-Jun Zha, Xian-Sheng Hua, Tao Mei, Jingdong W...
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...