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ITS
2010
Springer
157views Multimedia» more  ITS 2010»
14 years 13 days ago
A Computational Model of Accelerated Future Learning through Feature Recognition
Accelerated future learning, in which learning proceeds more effectively and more rapidly because of prior learning, is considered to be one of the most interesting measures of ro...
Nan Li, William W. Cohen, Kenneth R. Koedinger
IJCAI
2001
13 years 9 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
RSS
2007
176views Robotics» more  RSS 2007»
13 years 9 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
ICMLA
2008
13 years 9 months ago
New Insights into Learning Algorithms and Datasets
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
Jun Won Lee, Christophe G. Giraud-Carrier
WCE
2008
13 years 9 months ago
Design and Implementation of an E-Learning Model by Considering Learner's Personality and Emotions
Abstract Emotion, personality and individual differences are those effective parameters on human's activities such as learning. People with different personalities show differ...
Somayeh Fatahi, M. Kazemifard, Nasser Ghasem-Aghae...