We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...
The aim of the project we discuss in this paper is to develop a computational model of peer learning. We present an extensive analysis of peer learning dialogues, analysis on which...
Cynthia Kersey, Barbara Di Eugenio, Pamela W. Jord...
Learning from ambiguous training data is highly relevant in many applications. We present a new learning algorithm for classification problems where labels are associated with se...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...