As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment...
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...