Practical Compression with Model-Code Separation

Current compression systems incorporate a data model, however formed, deeply into the coding process, leading to difficulties of an architectural nature. This work contributes an alternative "Model-Code Separation" architecture for general compression, based on model-free coding and iterative message-passing algorithms over graphical models representing the modeling and coding aspects of compression in decoding. Systems following this architecture resolve important challenges posed by current systems, and stand to benefit further from advances in the understanding of data and the algorithms that process them.