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» A Theory for Memory-Based Learning
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IJON
2006
99views more  IJON 2006»
15 years 6 months ago
Learning vector quantization: The dynamics of winner-takes-all algorithms
Winner-Takes-All (WTA) prescriptions for Learning Vector Quantization (LVQ) are studied in the framework of a model situation: Two competing prototype vectors are updated accordin...
Michael Biehl, Anarta Ghosh, Barbara Hammer
NECO
2010
97views more  NECO 2010»
15 years 4 months ago
Rademacher Chaos Complexities for Learning the Kernel Problem
In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
Yiming Ying, Colin Campbell
TSMC
2011
210views more  TSMC 2011»
15 years 29 days ago
Fault Diagnosis in Discrete-Event Systems: Incomplete Models and Learning
— Most state-based approaches to fault diagnosis of discrete-event systems require a complete and accurate model of the system to be diagnosed. In this paper, we address the prob...
Raymond H. Kwong, David L. Yonge-Mallo
AIED
2007
Springer
16 years 7 days ago
The Effect of Problem Templates on Learning in Intelligent Tutoring Systems
: This paper proposes the notion of problem templates (PTs), a concept based on theories of memory and expertise. These mental constructs allow experts to quickly recognise problem...
Moffat Mathews, Antonija Mitrovic
AIED
2005
Springer
15 years 11 months ago
Computer Games as Intelligent Learning Environments: A River Ecosystem Adventure
Our goal in this work has been to bring together the entertaining and flow characteristics of video game environments with proven learning theories to advance the state of the art ...
Jason Tan, Chris Beers, Ruchi Gupta, Gautam Biswas