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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)
0.2: Automated Modeling and Nonlinear Axis Scaling - Leejay Wu (2005) (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" }
Citations (may not include all citations):472 Hierarchical mixture of experts and the EM algorithm - Jordan, Jacobs - 1994
450 Generalized additive models - Hastie, Tibshirani - 1990
372 The cascade-correlation learning architecture - Fahlman, Lebiere - 1990
244 Theory and practice of recursive identification (context) - Ljung, Soderstrom - 1986
228 Nonlinear dimensionality reduction by local linear embedding - Roweis, Saul - 2000
186 Projection pursuit regression (context) - Friedman, Stutzle - 1981
185 Numerical recipes in C: The art of scientific computing (context) - Press, Flannery et al. - 1989
149 Multivariate density estimation (context) - Scott - 1992
113 Locally weighted learning - Atkeson, Moore et al. - 1997
102 A tutorial on support vector regression - Smola, Sch - 1998
92 Probabilistic principal component analysis - Tipping, Bishop - 1999
92 A resource-allocating network for function interpolation (context) - Platt - 1991
78 Gaussian processes for regression - Williams, Rasmussen - 1996
68 An introduction to latent variable models (context) - Everitt - 1984
65 Model based control of a robot manipulator (context) - An, Atkeson et al. - 1988
64 EM algorithms for ML factor analysis (context) - Rubin, Thayer - 1982
56 Classical and modern regression with applications (context) - Myers - 2004
54 An alternative model for mixtures of experts - Xu, Jordan et al. - 1995
49 The UCI KDD archive (context) - Hettich, Bay - 1999
44 Variational inference for Bayesian mixtures of factor analys.. - Ghahramani, Beal - 2000
43 Using the Nystrom method to speed up kernel machines (context) - Williams, Seeger - 2001
42 Local regression: Automatic kernel carpentry - Hastie, Loader - 1993
41 SMEM algorithm for mixture models - Ueda, Nakano et al. - 2000
33 Advances in kernel methods: Support vector learning - olkopf, Burgess et al. - 1999
32 London: Chapman and Hall (context) - Gelman, Carlin et al. - 1995
32 Regression diagnostics (context) - Belsley, Kuh et al. - 1980
30 Aircraft control and simulation (context) - Stevens, Lewis - 2000
29 Support vector machine---reference manual - Saunders, Stitson et al. - 1998
27 Assessing the quality of learned local models - Schaal, Atkeson - 1994
20 New support vector algorithms - olkopf, Smola et al. - 2000
17 Efficient implementation of gaussian processes - Gibbs, Mackay - 1997
11 Optimal unsupervised learning in a single layer feedforward .. (context) - Sanger - 1989
10 Local adaptive subspace regression - Vijayakumar, Schaal - 1998
10 Local dimensionality reduction - Schaal, Vijayakumar et al. - 1998
9 RKHS based functional analysis for exact incremental learnin.. (context) - Vijayakumar, Ogawa - 1999
6 Receptive field weighted regression - Schaal, Atkeson - 1997
5 Neural networks for speech and image processing (context) - Perrone, Cooper - 1993
3 Perspectives in probability and statistics (context) - Wold - 1975
3 Are internal models of the entire body learnable (context) - D'Souza, Vijayakumar et al. - 2001
3 Supervised dimensionality reduction of intrinsically low-dim.. (context) - Vlassis, Motomura et al. - 2002
2 A statistical view of some chemometric tools (context) - Frank, Friedman - 1993
1 accepted June (context) - March - 2005
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