Image analysis – Learning systems
Reexamination Certificate
2008-06-10
2008-06-10
Mehta, Bhavesh M. (Department: 2624)
Image analysis
Learning systems
C382S128000, C382S224000, C706S015000
Reexamination Certificate
active
07386165
ABSTRACT:
A method and device having instructions for analyzing input data-space by learning classifiers include choosing a candidate subset from a predetermined training data-set that is used to analyze the input data-space. Candidates are temporarily added from the candidate subset to an expansion set to generate a new kernel space for the input data-space by predetermined repeated evaluations of leave-one-out errors for the candidates added to the expansion set. This is followed by removing the candidates temporarily added to the expansion set after the leave-one-out error evaluations are performed, and selecting the candidates to be permanently added to the expansion set based on the leave-one-out errors of the candidates temporarily added to the expansion set to determine the one or more classifiers.
REFERENCES:
patent: 5050222 (1991-09-01), Lee
patent: 5481269 (1996-01-01), Imhoff et al.
patent: 5734587 (1998-03-01), Backhaus et al.
patent: 5734739 (1998-03-01), Sheehan et al.
patent: 5796863 (1998-08-01), Lyon
patent: 5799100 (1998-08-01), Clarke et al.
patent: 5835901 (1998-11-01), Duvoisin et al.
patent: 5930803 (1999-07-01), Becker et al.
patent: 6327581 (2001-12-01), Platt
patent: 7020593 (2006-03-01), Hong et al.
patent: 7035467 (2006-04-01), Nicponski
patent: 2002/0010691 (2002-01-01), Chen
patent: 2005/0010445 (2005-01-01), Krishnan et al.
patent: 2007/0053563 (2007-03-01), Tu et al.
Leave-one-out procedures for nonparametric error estimates, Fukunaga, K.; Hummels, D.M.; Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 11, Issue 4, Apr. 1989 pp. 421-423.
Toward an optimal supervised classifier for the analysis of hyperspectral data, Dundar, M.M.; Landgrebe, D.A.; Geoscience and Remote Sensing, IEEE Transactions on, vol. 42, Issue 1, Jan. 2004 pp. 271-277.
Covariance matrix estimation and classification with limited training data, Hoffbeck, J.P.; Landgrebe, D.A.; Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 18, Issue 7, Jul. 1996 pp. 763-767.
An improved training algorithm for kernel Fisher discriminants, Mika, S.; Smola, A.; Scholkopf, B.; Proc. International Workshop on Artificial Intelligence and Statistics, Jan. 4-7, 2001, Key West, Florida.
An introduction to kernel-based learning algorithms Muller, K.-R.; Mika, S.; Ratsch, G.; Tsuda, K.; Scholkopf, B. Neural Networks, IEEE Transactions on vol. 12, No. 2, Mar. 2001 pp. 181-198.
Mika S et al, “An Improved Training Algorithm for Kernel Fisher Discriminants”, International Workshop on Artificial Intelligence and Statistics, Jan. 4, 2001, pp. 1-7.
Smola A.J. et al, “Sparse Greedy Matrix Approximation for Machine Learning”, Proceedings of the 17thInternational Conference on Machine Learning, Stanford University, CA, USA.
Williams C et al, “Using the Nyström Method to Speed Up Kernel Machines”,Advances in Neural Information Processing Systems, vol. 13, 2001, pp. 682-688.
Franc V et al, “Greedy Algorithm for a Training Set Reduction in the Kernel Methods”,Lecture Notes in Computer Science, Springer Verlag, New York, NY, US, vol. 2756, Aug. 25, 2003, pp. 426-433.
Schölkopf B et al, “Learning with Kernels”, 2002, MIT Press, Cambridge, section 12.2.1, pp. 366-369.
Tresp V., “Scaling Kernel-Based Systems to Large Data Sets”,Data Mining and Knowledge Discovery, vol. 5, No. 3, 2001, pp. 1-18.
International Search Report including Notification of Transmittal of the International Search Report, International Search Report, and Written Opinion of the International Searching Authority.
Bi Jinbo
Dundar Murat
Fung Glenn
Rao R. Bharat
Mehta Bhavesh M.
Seth Manav
Siemens Medical Solutions USA , Inc.
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