Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
It is known that modeling an information source via a symbolic dynamical system evolving over the unit interval, leads to a natural lossless compression scheme attaining the entro...
This paper considers online compression algorithms that use at most polylogarithmic space (plogon). These algorithms correspond to compressors in the data stream model. We study th...
Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binar...