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CIKM
2009
Springer
14 years 3 months ago
Scalable learning of collective behavior based on sparse social dimensions
The study of collective behavior is to understand how individuals behave in a social network environment. Oceans of data generated by social media like Facebook, Twitter, Flickr a...
Lei Tang, Huan Liu
ICML
2006
IEEE
14 years 9 months ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik
ATAL
2006
Springer
14 years 10 days ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
SGAI
2010
Springer
13 years 6 months ago
Hierarchical Traces for Reduced NSM Memory Requirements
This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based ...
Torbjørn S. Dahl
ECTEL
2006
Springer
14 years 8 days ago
iCamp - The Educational Web for Higher Education
iCamp is an EC-funded research project in the area of Technology Enhanced Learning (TEL) that aims to support collaboration and social networking across systems, countries and disc...
Barbara Kieslinger, Fridolin Wild, Onur Ihsan Arsu...