ELHOSEINY, ELGAMMAL: OVERLAPPING DOMAIN COVER FOR KERNEL MACHINES 1 Overlapping Domain Cover for Scalable and Accurate Regression Kernel Machines
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چکیده
In this paper, we present the Overlapping Domain Cover (ODC) notion for kernel machines, as a set of overlapping subsets of the data that covers the entire training set and optimized to be spatially cohesive as possible. We propose an efficient ODC framework, which is applicable to various regression models and in particular reduces the complexity of Twin Gaussian Processes (TGP) regression from cubic to quadratic. We also theoretically justified the idea behind our method. We validated and analyzed our method on three human pose estimation datasets and interesting findings are discussed.
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تاریخ انتشار 2015