We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Analysis of postgenomic biological data (such as microarray and SNP data) is a subtle art and science, and the statistical methods most commonly utilized sometimes prove inadequat...
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
We introduce a new metaphor for learning spatial relations--the 3D puzzle. With this metaphor users learn spatial relations by assembling a geometric model themselves. For this pu...
Bernhard Preim, Felix Ritter, Oliver Deussen, Thom...
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...