{"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/accelerating-convergence-of-replica-exchange","title":"Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction","arxiv_id":"2010.01084","date":"2020-10-02","proceeding":"ICLR 2021 1","authors":["Wei Deng","Qi Feng","Georgios Karagiannis","Guang Lin","Faming Liang"],"abstract":"Replica exchange stochastic gradient Langevin dynamics (reSGLD) has shown promise in accelerating the convergence in non-convex learning; however, an excessively large correction for avoiding biases from noisy energy estimators has limited the potential of the acceleration. To address this issue, we study the variance reduction for noisy energy estimators, which promotes much more effective swaps. Theoretically, we provide a non-asymptotic analysis on the exponential acceleration for the underlying continuous-time Markov jump process; moreover, we consider a generalized Girsanov theorem which includes the change of Poisson measure to overcome the crude discretization based on the Gr\\\"{o}wall's inequality and yields a much tighter error in the 2-Wasserstein ($\\mathcal{W}_2$) distance. Numerically, we conduct extensive experiments and obtain the state-of-the-art results in optimization and uncertainty estimates for synthetic experiments and image data.","url_abs":"https://arxiv.org/abs/2010.01084v2","url_pdf":"https://arxiv.org/pdf/2010.01084v2.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":"accelerating-convergence-of-replica-exchange","repo_url":"https://github.com/WayneDW/Variance_Reduced_Replica_Exchange_SGMCMC","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2010.01084","atlas_url":"https://app.syntology.ai/?focus=2010.01084","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.01084"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/WayneDW/Variance_Reduced_Replica_Exchange_SGMCMC","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"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":1,"samples":[{"code_sha256_prefix":"bcda45461bf9fde7","entry":"number_digits","repo":"WayneDW/Variance_Reduced_Replica_Exchange_SGMCMC","repo_kind":"official","path":"uncertainty_test.py","file_url":"https://github.com/WayneDW/Variance_Reduced_Replica_Exchange_SGMCMC/blob/HEAD/uncertainty_test.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"bcda45461bf9fde7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}