This paper introduces three new contributions to the problems of image classification and image search. First, we propose a new image patch quantization algorithm. Other competitiv...
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
In this paper we investigate random forest based language model adaptation. Large amounts of out-of-domain data are used to grow the decision trees while very small amounts of in-...
This paper presents techniques to apply semi-CRFs to Named Entity Recognition tasks with a tractable computational cost. Our framework can handle an NER task that has long named e...
Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...