Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Models of activity structure for unconstrained environments are generally not available a priori. Recent representational approaches to this end are limited by their computational...
Raffay Hamid, Siddhartha Maddi, Aaron F. Bobick, I...
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
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 study gender discrimination of human faces using a combination of psychophysical classification and discrimination experiments together with methods from machine learning. We r...
Felix A. Wichmann, Arnulf B. A. Graf, Eero P. Simo...