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Incremental Online Learning in High Dimensions (2005)  (Make Corrections)  
Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal



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Abstract: this article, however, is problematic, as it requires a careful selection of initial ridge regression parameters to stabilize the highly rank-deficient full covariance matrix of the input data, and it is easy to create too much bias or too little numerical stabilization initially, which can trap the local distance metric adaptation in local minima.While the LWPR algorithm just computes about a factor 10 times longer for the 20D experiment in comparison to the 2D experiment, RFWR requires a... (Update)

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2.6:   Incremental Online Learning in High Dimensions - Vijayakumar, D'Souza, Schaal (2005)   (Correct)
0.2:   Constructive Incremental Learning From Only Local Information - Schaal, Atkeson (1997)   (Correct)
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BibTeX entry:   (Update)

@misc{ vijayakumar-incremental,
  author = "Sethu Vijayakumar and Aaron D'Souza and Stefan Schaal",
  title = "Incremental Online Learning in High Dimensions",
  url = "citeseer.ist.psu.edu/article/vijayakumar05incremental.html" }
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