Kernel machines (e.g. SVM, KLDA) have shown state-ofthe-art performance in several visual classification tasks. The classification performance of kernel machines greatly depends o...
This paper is focused on algorithmic issues for biometric face verification (i.e., given an image of the face and an identity claim, decide whether they correspond to each other o...
Javier Ortega-Garcia, Joaquin Gonzalez-Rodriguez, ...
Recent empirical work has shown that combining predictors can lead to significant reduction in generalization error. The individual predictors (weak learners) can be very simple, ...
The Non-negative Matrix Factorization technique (NMF) has been recently proposed for dimensionality reduction. NMF is capable to produce a region- or partbased representation of o...
Bernt Schiele, David Guillamet, Jordi Vitrià...
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...