Background: Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these...
Hongbo Zhu, Francisco S. Domingues, Ingolf Sommer,...
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Abstract In recent years, automatic human action recognition has been widely researched within the computer vision and image processing communities. Here we propose a realtime, emb...
Hongying Meng, Michael Freeman, Nick Pears, Chris ...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
: We propose a new nonparametric family of oscillation heuristics for improving linear classifiers in the two-group discriminant problem. The heuristics are motivated by the intuit...