Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
In this paper, we suggest to model priors on human motion by means of nonparametric kernel densities. Kernel densities avoid assumptions on the shape of the underlying distribution...
Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-...
We recently developed a new benchmark for steganography, underpinned by the square root law of capacity, called Steganographic Fisher Information (SFI). It is related to the multip...
We study retinal curvature estimation from multiple images that provides the fundamental geometry of human retina. We use an affine camera model due to its simplicity, linearity, ...
We consider the problem of binary classification where the classifier may abstain instead of classifying each observation. The Bayes decision rule for this setup, known as Chow...
Yves Grandvalet, Alain Rakotomamonjy, Joseph Keshe...