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» Two-Stage Machine Learning model for guideline development
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ICML
2009
IEEE
14 years 3 months ago
Using fast weights to improve persistent contrastive divergence
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...
Tijmen Tieleman, Geoffrey E. Hinton
AIIA
2009
Springer
14 years 3 months ago
Analyzing Interactive QA Dialogues Using Logistic Regression Models
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...
ESSMAC
2003
Springer
14 years 1 months ago
Filtered Gaussian Processes for Learning with Large Data-Sets
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...
ICALT
2006
IEEE
14 years 2 months ago
The e-Learning Assessment Landscape
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...
COLT
1992
Springer
14 years 24 days ago
Language Learning from Stochastic Input
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...
Shyam Kapur, Gianfranco Bilardi