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- W2765930498 abstract "We examine the Mahalanobis-distance based kernel-RX (KRX) algorithm for anomaly detection, and find that it can exhibit an unfortunate phenomenon: the anomalousness, for points far from the training data, can decrease with increasing distance. We demonstrate this directly for a few special cases, and provide a more general argument that applies in the large bandwidth regime." @default.
- W2765930498 created "2017-11-10" @default.
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- W2765930498 date "2016-08-01" @default.
- W2765930498 modified "2023-10-16" @default.
- W2765930498 title "Cracks in KRX: When more distant points are less anomalous" @default.
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- W2765930498 doi "https://doi.org/10.1109/whispers.2016.8071717" @default.
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