Making decisions based on a linear combination L of features is of course very common in pattern recognition. For distinguishing between two hypotheses or classes, the test is of ...
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the...
We simultaneously approach two tasks of nonlinear discriminant analysis and kernel selection problem by proposing a unified criterion, Fisher+Kernel Criterion. In addition, an eff...
Shu Yang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Cha...
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...