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==Introduction== | ==Introduction== | ||
This paper tries to propose a method to learn mappings from high dimensional data to binary codes. One of the main advantages of using binary space is one can do exact KNN classification in sublinear time. | This paper tries to propose a method to learn mappings from high dimensional data to binary codes. One of the main advantages of using binary space is one can do exact KNN classification in sublinear time. Like other metric learning method this paper also tries to optimize some cost function which is based one a similarity measure between data points. | ||
Revision as of 23:34, 6 July 2013
Introduction
This paper tries to propose a method to learn mappings from high dimensional data to binary codes. One of the main advantages of using binary space is one can do exact KNN classification in sublinear time. Like other metric learning method this paper also tries to optimize some cost function which is based one a similarity measure between data points.