{"paper":{"title":"On principles of large deviation and selected data compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","math.PR"],"primary_cat":"cs.IT","authors_text":"Izabella Stuhl, Yuri Suhov","submitted_at":"2016-04-24T01:46:37Z","abstract_excerpt":"The Shannon Noiseless coding theorem (the data-compression principle) asserts that for an information source with an alphabet $\\mathcal X=\\{0,\\ldots ,\\ell -1\\}$ and an asymptotic equipartition property, one can reduce the number of stored strings $(x_0,\\ldots ,x_{n-1})\\in {\\mathcal X}^n$ to $\\ell^{nh}$ with an arbitrary small error-probability. Here $h$ is the entropy rate of the source (calculated to the base $\\ell$). We consider further reduction based on the concept of utility of a string measured in terms of a rate of a weight function. The novelty of the work is that the distribution of m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.06971","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}