{"paper":{"title":"On the Sublinear Regret of Distributed Primal-Dual Algorithms for Online Constrained Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Michael M. Zavlanos, Soomin Lee","submitted_at":"2017-05-31T15:02:58Z","abstract_excerpt":"This paper introduces consensus-based primal-dual methods for distributed online optimization where the time-varying system objective function $f_t(\\mathbf{x})$ is given as the sum of local agents' objective functions, i.e., $f_t(\\mathbf{x}) = \\sum_i f_{i,t}(\\mathbf{x}_i)$, and the system constraint function $\\mathbf{g}(\\mathbf{x})$ is given as the sum of local agents' constraint functions, i.e., $\\mathbf{g}(\\mathbf{x}) = \\sum_i \\mathbf{g}_i (\\mathbf{x}_i) \\preceq \\mathbf{0}$. At each stage, each agent commits to an adaptive decision pertaining only to the past and locally available informatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.11128","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"}