{"paper":{"title":"Non-Convex Compressed Sensing Using Partial Support Information","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","math.OC"],"primary_cat":"cs.IT","authors_text":"Hassan Mansour, Navid Ghadermarzy, Ozgur Yilmaz","submitted_at":"2013-11-15T08:56:54Z","abstract_excerpt":"In this paper we address the recovery conditions of weighted $\\ell_p$ minimization for signal reconstruction from compressed sensing measurements when partial support information is available. We show that weighted $\\ell_p$ minimization with $0<p<1$ is stable and robust under weaker sufficient conditions compared to weighted $\\ell_1$ minimization. Moreover, the sufficient recovery conditions of weighted $\\ell_p$ are weaker than those of regular $\\ell_p$ minimization if at least $50%$ of the support estimate is accurate. We also review some algorithms which exist to solve the non-convex $\\ell_p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1311.3773","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"}