The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
With traditional Question Answering (QA) systems having reached nearly satisfactory performance, an emerging challenge is the development of successful Interactive Question Answeri...
Manuel Kirschner, Raffaella Bernardi, Marco Baroni...
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...
Assessment is one of the more established areas of e-learning. However, it cannot be described as mature due to the disparate nature of the tools and standards available. As part ...
David E. Millard, Christopher Bailey, Hugh C. Davi...
Language learning from positive data in the Gold model of inductive inference is investigated in a setting where the data can be modeled as a stochastic process. Specifically, the...