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- W2323059508 abstract "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." @default.
- W2323059508 created "2016-06-24" @default.
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- W2323059508 date "2015-01-01" @default.
- W2323059508 modified "2023-09-28" @default.
- W2323059508 title "Overlapping Domain Cover for Scalable and Accurate Regression Kernel Machines" @default.
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- W2323059508 doi "https://doi.org/10.5244/c.29.94" @default.
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