We present a method for visual classification of actions and events captured from an egocentric point of view. The method tackles the challenge of a moving camera by creating defor...
Metaprogramming adds new expressive power to logic programming which can be advantageous to transfer to the field of deductive databases. We propose metaprogramming as a way to mo...
In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended p...
Ming Li, Sanqing Hu, Shih-Hsi Liu, Sung Baang, Yu ...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang