—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A B) defined over pairs of matrices A B base...
We present a systematic comparison of machine learning methods applied to the problem of fully automatic recognition of facial expressions, including AdaBoost, support vector mach...
Gwen Littlewort, Marian Stewart Bartlett, Ian R. F...
For two-class discrimination, Ref. [1] claimed that, when covariance matrices of the two classes were unequal, a (class) unbalanced dataset had a negative effect on the performanc...