We present a new algorithm for learning a convex set in n-dimensional space given labeled examples drawn from any Gaussian distribution. The complexity of the algorithm is bounded ...
This paper develops a novel and efficient dimension reduction scheme--Fast Adaptive Discriminant Analysis (FADA). FADA can find a good projection with adaptation to different sampl...
In this paper, we address the relatively unexplored problem of classifying texture surfaces undergoing significant levels of non-rigid deformation. State-of-the-art texture classi...
This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and ...
A measure of stability for a wide class of pattern recognition algorithms is introduced to cope with overfitting in classification problems. Based on this concept, constructive me...