{"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/doubly-robust-bayesian-inference-for-non-1","title":"Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with $β$-Divergences","arxiv_id":"1806.02261","date":"2018-06-06","proceeding":"NeurIPS 2018","authors":["Jeremias Knoblauch","Jack Jewson","Theodoros Damoulas"],"abstract":"We present the very first robust Bayesian Online Changepoint Detection\nalgorithm through General Bayesian Inference (GBI) with $\\beta$-divergences.\nThe resulting inference procedure is doubly robust for both the parameter and\nthe changepoint (CP) posterior, with linear time and constant space complexity.\nWe provide a construction for exponential models and demonstrate it on the\nBayesian Linear Regression model. In so doing, we make two additional\ncontributions: Firstly, we make GBI scalable using Structural Variational\napproximations that are exact as $\\beta \\to 0$. Secondly, we give a principled\nway of choosing the divergence parameter $\\beta$ by minimizing expected\npredictive loss on-line. Reducing False Discovery Rates of CPs from more than\n90% to 0% on real world data, this offers the state of the art.","url_abs":"http://arxiv.org/abs/1806.02261v2","url_pdf":"http://arxiv.org/pdf/1806.02261v2.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":"abstracts"},"code_links":[{"paper_slug":"doubly-robust-bayesian-inference-for-non-1","repo_url":"https://github.com/alan-turing-institute/bocpdms","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"bayesian-inference","task_name":"Bayesian Inference"},{"task_slug":"change-point-detection","task_name":"Change Point Detection"}],"methods":[{"method_slug":"linear-regression","method_name":"Linear Regression"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1806.02261","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.02261"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/alan-turing-institute/bocpdms","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":2},"by_repo_kind":{"official":{"samples":2,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"9276fd201299bcab","entry":"load_bee_data","repo":"alan-turing-institute/bocpdms","repo_kind":"official","path":"bee_waggle_ICML18.py","file_url":"https://github.com/alan-turing-institute/bocpdms/blob/HEAD/bee_waggle_ICML18.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9276fd201299bcab"}},{"code_sha256_prefix":"4254877a92742361","entry":"load_nile_data","repo":"alan-turing-institute/bocpdms","repo_kind":"official","path":"nile_ICML18.py","file_url":"https://github.com/alan-turing-institute/bocpdms/blob/HEAD/nile_ICML18.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"4254877a92742361"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}