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Chapter and Conference Paper
Reducing Hubness for Kernel Regression
In this paper, we point out that hubness—some samples in a high-dimensional dataset emerge as hubs that are similar to many other samples—influences the performance of kernel regression. Because the dimension of ...
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Chapter and Conference Paper
Ridge Regression, Hubness, and Zero-Shot Learning
This paper discusses the effect of hubness in zero-shot learning, when ridge regression is used to find a map** between the example space to the label space. Contrary to the existing approach, which attempts...