This paper describes the creation of a state-of-the-art answer type detection system capable of recognizing more than 200 different expected answer types with greater than 85% pre...
The goal of this paper is to investigate to what extent a rule learning heuristic can be learned from experience. Our basic approach is to learn a large number of rules and record ...
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...