Clustering and classification employing softmax function...

Details Clustering and classification employing softmax function... Clustering and classification employing softmax function...

2008-10-14

2011-11-22

Holmes, Michael B (Department: 2129)

Data processing: artificial intelligence

Neural network

Learning task

C706S046000, C708S277000

Reexamination Certificate

active

08065246

ABSTRACT:
A function optimization method includes the operations of: constructing an upper bound using a double majorization bounding process to a sum-of-exponentials function including a summation of exponentials of the form∑k=1K⁢ⅇβkT⁢x;optimizing the constructed upper bound respective to parameters β to generate optimized parameters β; and outputting the optimized sum-of-exponentials function represented at least by the optimized parameters β. An inference process includes the operations of: invoking the function optimization method respective to a softmax function constrained by discrete observations y defining categorization observation conditioned by continuous variables x representing at least one input object; and applying the optimized softmax function output by the invocation of the softmax function optimization method to the continuous variables x representing at least one input object to generate classification probabilities.

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