Rate-Distortion Bounds for Kernel-Based Distortion Measures

Kernel methods have been used for turning linear learning algorithms into nonlinear ones. These nonlinear algorithms measure distances between data points by the distance in the kernel-induced feature space. In lossy data compression, the optimal tradeoff between the number of quantized points and t...

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Bibliographic Details
Main Author: Kazuho Watanabe
Format: Article
Language:English
Published: MDPI AG 2017-07-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/19/7/336