In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Abstract. Many learning methods ignore domain knowledge in synthesis of concept approximation. We propose to use hierarchical schemes for learning approximations of complex concept...
Jan G. Bazan, Sinh Hoa Nguyen, Hung Son Nguyen, An...
Abstract. This paper studies a Bayesian framework for density modeling with mixture of exponential family distributions. Variational Bayesian Dirichlet-Multinomial allocation (VBDM...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
Obtaining large volumes of inference knowledge, such as entailment rules, has become a major factor in achieving robust semantic processing. While there has been substantial resea...
Our objective is to model the visual manifold of object appearance corresponding to geometric transformation. We learn a generative model for object appearance where the appearanc...