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• W2950221323 abstract "Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance." @default.
• W2950221323 created "2019-06-27" @default.
• W2950221323 creator A5029628745 @default.
• W2950221323 creator A5035043292 @default.
• W2950221323 date "2006-09-21" @default.
• W2950221323 modified "2023-10-13" @default.
• W2950221323 title "Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising" @default.
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• W2950221323 hasPublicationYear "2006" @default.
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