We consider the problem of structured classification, where the task is to predict a label y from an input x, and y has meaningful internal structure. Our framework includes super...
Peter L. Bartlett, Michael Collins, Benjamin Taska...
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
Abstract: Suppose two judges each classify a group of objects into one of several nominal categories. It has been observed in the literature that, for fixed observed agreement betw...
We present an efficient method within an active vision framework for recognizing objects which are ambiguous from certain viewpoints. The system is allowed to reposition the camer...
Hermann Borotschnig, Lucas Paletta, Manfred Prantl...
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...