Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Given an image sequence of a scene consisting of multiple rigidly moving objects, multi-body structure-and-motion (MSaM) is the task to segment the image feature tracks into the d...
Selectional preferences have a long history in both generative and computational linguistics. However, since the publication of Resnik's dissertation in 1993, a new approach ...
The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A major drawback of the SOM has been the lack of a theoretically justified criterion for model se...
This article proposes a method for learning object templates
composed of local sketches and local textures, and
investigates the relative importance of the sketches and textures
...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...