Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2011-01-25
2011-01-25
Holmes, Michael B. (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
C706S017000, C706S025000, C706S026000
Reexamination Certificate
active
07877339
ABSTRACT:
A method and system of creating an approximate kernel matrix to train a kernel machine. In one embodiment of the invention, a set of kernel machine training data is partitioned into a set of partitioned training data based on a set of partition parameters. The set of partition parameters includes one or more of, an axis-aligned grid location, or an axis-aligned grid resolution in one embodiment of the invention. A partition matrix that approximates a kernel machine kernel matrix is created from the set of partitioned training data and the partition matrix is used to train a kernel machine in one embodiment of the invention.
REFERENCES:
patent: 6944602 (2005-09-01), Cristianini
Cristianini in view of Drineas et al. (Drineas), Approximating a Gram Matrix for Improved Kernel-Based Learning (Extended Abstract), COLT 2005, LNAI 3559, pp. 323-337, 2005.
Grauman et al. (Grauman), The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, Proceedings of the IEEE International Conference on Computer Vision, Beijing, China, Oct. 2005.
Blakely , Sokoloff, Taylor & Zafman LLP
Brown, Jr. Nathan H
Holmes Michael B.
Intel Corporation
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