{"paper":{"title":"Faster Parallel Solver for Positive Linear Programs via Dynamically-Bucketed Selective Coordinate Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"cs.DS","authors_text":"Di Wang, Michael Mahoney, Nishanth Mohan, Satish Rao","submitted_at":"2015-11-20T01:10:13Z","abstract_excerpt":"We provide improved parallel approximation algorithms for the important class of packing and covering linear programs. In particular, we present new parallel $\\epsilon$-approximate packing and covering solvers which run in $\\tilde{O}(1/\\epsilon^2)$ expected time, i.e., in expectation they take $\\tilde{O}(1/\\epsilon^2)$ iterations and they do $\\tilde{O}(N/\\epsilon^2)$ total work, where $N$ is the size of the constraint matrix and $\\epsilon$ is the error parameter, and where the $\\tilde{O}$ hides logarithmic factors. To achieve our improvement, we introduce an algorithmic technique of broader in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.06468","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"}