Neural Computation
February 2013, Vol. 25, No. 2, Pages 532-548
(doi: 10.1162/NECO_a_00401)
The Kernel Semi–Least Squares Method for Sparse Distance Approximation
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Abstract
We extend the semi–least squares problem defined by Rao and Mitra (1971) to the kernel semi–least squares problem. We introduce subset projection, a technique that produces a solution to this problem. We show how the results of subset projection can be used to approximate a computationally expensive distance metric.