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Abstract: Ideally pattern recognition machines provide constant output when the inputs are transformed under a group G of desired invariances. These invariances can be achieved by enhancing the training data to include examples of inputs transformed by elements of G, while leaving the corresponding targets unchanged. Alternatively the cost function for training can include a regularization term that penalizes changes in the output when the input is transformed under the group. This paper relates... (Update)
Context of citations to this paper: More
.... 6] 7] Their use has been justified through regularization theory in connection with their energy minimization properties [8] 9] [10]. A radial basis function approximation in p dimensions (x # R p ) has the generic form f(x) X k#Z a k #(#x x k #) 1) where...
...adding the virtual examples L t x i in the training set. Indeed the two approaches are related and some equivalence can be shown [6]. So why not just add virtual examples This is the idea of the Virtual Support Vector (VSV) method [10] The reason is the following: if a...
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BibTeX entry: (Update)
Todd K. Leen. From data distributions to regularization in invariant learning. Neural Computation, 3(1):135--143, 1991. http://citeseer.ist.psu.edu/leen95from.html More
@inproceedings{ leen95from,
author = "Todd K. Leen",
title = "From Data Distributions to Regularization in Invariant Learning",
booktitle = "Advances in Neural Information Processing Systems",
volume = "7",
publisher = "The {MIT} Press",
editor = "G. Tesauro and D. Touretzky and T. Leen",
pages = "223--230",
year = "1995",
url = "citeseer.ist.psu.edu/leen95from.html" }
Citations (may not include all citations):57 Training with noise is equivalent to Tikhonov regularization - Bishop - 1995
45 Handwritten digit recognition with a back-propagation networ.. - Le Cun, Boser et al. - 1990
30 Lie Groups and Algebras with Applications to Physics (context) - Sattinger, Weaver - 1986
13 A method for learning from hints (context) - Abu-Mostafa - 1993
6 Encoding geometric invariances in higherorder neural network.. (context) - Giles, Griffin et al. - 1988
2 Tanget prop - a formalism for specifying selected invariance.. (context) - Simard, Victorri et al. - 1992
The graph only includes citing articles where the year of publication is known.
Documents on the same site (http://cse.ogi.edu/~tleen/publications.html): More
Exact and Perturbation Solutions for the Ensemble Dynamics - Leen (1998) (Correct)
From Data Distributions to Regularization in Invariant Learning - Leen (1995) (Correct)
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