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аналитика - Rate-Distortion Theory
Alternate Learning and Compression Approaching the Rate-Distortion Bound
This paper explores the connection between backward-adaptive lossy compression and online learning, specifically focusing on the Natural Type Selection (NTS) algorithm and its ability to approach the rate-distortion bound by balancing exploration and exploitation.
Distributed Source Coding, Multiple Description Coding, and Source Coding with Side Information at Decoders Using Constrained-Random Number Generators: A Unified Approach to Characterizing Multi-letter Rate-Distortion Regions for General Correlated Sources
This paper presents a unified framework for distributed source coding, multiple description coding, and source coding with side information at decoders, characterizing their multi-letter rate-distortion regions for general correlated sources using constrained-random number generators.
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