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» Relational Reinforcement Learning
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193
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QRE
2010
129views more  QRE 2010»
15 years 5 months ago
Improving quality of prediction in highly dynamic environments using approximate dynamic programming
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Rajesh Ganesan, Poornima Balakrishna, Lance Sherry
196
Voted
SIGIR
2011
ACM
14 years 9 months ago
Social context summarization
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...
281
Voted
ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
132
Voted
AIED
2007
Springer
16 years 1 months ago
Explaining Self-Explaining: A Contrast between Content and Generation
Self-explaining has been repeatedly shown to result in positive learning outcomes for students in a wide variety of disciplines. However, there are two potential accounts for why s...
Robert G. M. Hausmann, Kurt VanLehn
163
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IWINAC
2005
Springer
16 years 11 days ago
Spatial navigation based on novelty mediated autobiographical memory
This paper presents a method for spatial navigation performed mainly on past experiences. The past experiences are remembered in their temporal context, i.e. as episodes of events....
Emilia I. Barakova, Tino Lourens