Abstract. Semi-supervised learning and ensemble learning are two important learning paradigms. The former attempts to achieve strong generalization by exploiting unlabeled data; th...
Abstract. A new theoretical framework for the analysis of linear combiners is presented in this paper. This framework extends the scope of previous analytical models, and provides ...
Abstract. This paper investigates the use of diverse data fusion methods to improve the performance of the passage retrieval component in a question answering system. Our results o...
Artificial neural networks play an important role for pattern recognition tasks. However, due to poor comprehensibility of the learned network, and the inability to represent expl...
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...