This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
—This paper presents a method to find salient image points in images with regular patterns based on deviations from the overall manifold structure. The two main contributions ar...
We propose a new method to retrieve similar face images from large face databases. The proposed method extracts a set of Haar-like features, and integrates these features with sup...
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...