{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-markovian-incremental-stochastic","title":"A Markovian Incremental Stochastic Subgradient Algorithm","arxiv_id":"2108.07900","date":"2021-08-17","proceeding":null,"authors":["Rafael Massambone","Eduardo F. Costa","Elias S. Helou"],"abstract":"A stochastic incremental subgradient algorithm for the minimization of a sum of convex functions is introduced. The method sequentially uses partial subgradient information and the sequence of partial subgradients is determined by a general Markov chain. This makes it suitable to be used in networks where the path of information flow is stochastically selected. We prove convergence of the algorithm to a weighted objective function where the weights are given by the Ces\\`aro limiting probability distribution of the Markov chain. Unlike previous works in the literature, the Ces\\`aro limiting distribution is general (not necessarily uniform), allowing for general weighted objective functions and flexibility in the method.","url_abs":"https://arxiv.org/abs/2108.07900v2","url_pdf":"https://arxiv.org/pdf/2108.07900v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"a-markovian-incremental-stochastic","repo_url":"https://github.com/RMassambone/MISSA","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}