An adaptive approach to learning optimal neighborhood kernels
Learning an optimal kernel plays a pivotal role in kernel-based methods. Recently, an approach called optimal neighborhood kernel learning (ONKL) has been proposed, showing promising classification performance. It assumes that the optimal kernel will resi
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|Source:||IEEE Transactions on Cybernetics|
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