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Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets
(Ieee Computer Soc, 2015-05-01)
We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational ...
Learning obstacle avoidance with an operant behavioral model
(Massachusetts Institute of Technology, 2004)
Artificial intelligence researchers have been attracted by the idea of having robots learn how to accomplish a task, rather than being told explicitly. Reinforcement learning has been proposed as an appealing framework to ...
Learning strategies scale: adaptation to Portuguese and factor structure
(BioMed Central, 2018)
Abstract
Since learning strategies seem to be an important set of variables to explain the effectiveness of training and e-learning in organizations is here to stay, this paper aimed to analyze the factor ...
Learning strategies evaluation in students with attention deficit hyperactivity disorder
(2013)
This study aim to verify the use of learning strategies in students of the elementary level presenting interdisciplinary diagnosis of attention dei cit hyperactivity disorder (ADHD). Nine students, male gender, attending ...
Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?
(Elsevier, 2015)
We develop a general equilibrium asset pricing model under incomplete information and rational learning in order to understand the unexplained predictability of option prices. In our model, the fundamental dividend growth ...