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...
In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...