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ITS
2010
Springer
136views Multimedia» more  ITS 2010»
15 years 11 months ago
Do Micro-Level Tutorial Decisions Matter: Applying Reinforcement Learning to Induce Pedagogical Tutorial Tactics
Pedagogical tutorial tactics are policies for a tutor to decide the next action when there are multiple actions available. When the contents were controlled so as to be the same, l...
Min Chi, Kurt VanLehn, Diane J. Litman
ECAI
2008
Springer
15 years 8 months ago
Belief revision with reinforcement learning for interactive object recognition
From a conceptual point of view, belief revision and learning are quite similar. Both methods change the belief state of an intelligent agent by processing incoming information. Ho...
Thomas Leopold, Gabriele Kern-Isberner, Gabriele P...
UAI
2003
15 years 8 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
ICANN
2010
Springer
15 years 8 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel
JMLR
2006
156views more  JMLR 2006»
15 years 6 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...