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ICML
2005
IEEE
15 years 11 months ago
Hedged learning: regret-minimization with learning experts
In non-cooperative multi-agent situations, there cannot exist a globally optimal, yet opponent-independent learning algorithm. Regret-minimization over a set of strategies optimiz...
Yu-Han Chang, Leslie Pack Kaelbling
ICALT
2006
IEEE
15 years 4 months ago
Effective Analysis and Design of Computer-Supported Learning System
The analysis phase constitutes an essential step in the development of information systems. Nevertheless, learning materials design activities currently have reduced the analysis ...
David Díez Cebollero, Camino Fernánd...
ICALT
2006
IEEE
15 years 4 months ago
Metadata Challenges for Situational Properties of Learning Objects
raction of free-standing metadata describing learning objects is typified by an analytical model which primarily focuses on the encoding of discrete properties pertaining to the ...
Baden Hughes, Roderick A. Farmer
ICALT
2006
IEEE
15 years 4 months ago
Automatic Generation of Metadata for Learning Objects
Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as “learning objective”', “related concept”, etc. Manually ...
Paramjeet Singh Saini, Marco Ronchetti, Diego Sona
COLT
1993
Springer
15 years 2 months ago
Learning from a Population of Hypotheses
We introduce a new formal model in which a learning algorithm must combine a collection of potentially poor but statistically independent hypothesis functions in order to approxima...
Michael J. Kearns, H. Sebastian Seung