{"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/projective-preferential-bayesian-optimization","title":"Projective Preferential Bayesian Optimization","arxiv_id":"2002.03113","date":"2020-02-08","proceeding":"ICML 2020 1","authors":["Petrus Mikkola","Milica Todorović","Jari Järvi","Patrick Rinke","Samuel Kaski"],"abstract":"Bayesian optimization is an effective method for finding extrema of a black-box function. We propose a new type of Bayesian optimization for learning user preferences in high-dimensional spaces. The central assumption is that the underlying objective function cannot be evaluated directly, but instead a minimizer along a projection can be queried, which we call a projective preferential query. The form of the query allows for feedback that is natural for a human to give, and which enables interaction. This is demonstrated in a user experiment in which the user feedback comes in the form of optimal position and orientation of a molecule adsorbing to a surface. We demonstrate that our framework is able to find a global minimum of a high-dimensional black-box function, which is an infeasible task for existing preferential Bayesian optimization frameworks that are based on pairwise comparisons.","url_abs":"https://arxiv.org/abs/2002.03113v4","url_pdf":"https://arxiv.org/pdf/2002.03113v4.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":"projective-preferential-bayesian-optimization","repo_url":"https://github.com/AaltoPML/PPBO","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"projective-preferential-bayesian-optimization","repo_url":"https://github.com/P-Mikkola/PPBO","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"bayesian-optimization","task_name":"Bayesian Optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2002.03113","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.03113"}},"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/P-Mikkola/PPBO","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/AaltoPML/PPBO","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":9},"by_repo_kind":{"listed":{"samples":9,"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":"bbf4831cff62777c","entry":"EI","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/acquisition.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/acquisition.py","link_basis":"harvester_set","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":"bbf4831cff62777c"}},{"code_sha256_prefix":"03f203f5d55f326b","entry":"EI_to_maximize","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/acquisition.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/acquisition.py","link_basis":"harvester_set","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":"03f203f5d55f326b"}},{"code_sha256_prefix":"d1bf8cda6854aa33","entry":"SE_kernel","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/kernels.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/kernels.py","link_basis":"harvester_set","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":"d1bf8cda6854aa33"}},{"code_sha256_prefix":"d2966880e7b5a6db","entry":"alpha_bounds","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/misc.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/misc.py","link_basis":"harvester_set","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":"d2966880e7b5a6db"}},{"code_sha256_prefix":"e2ec08ac02d66882","entry":"d","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/kernels.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/kernels.py","link_basis":"harvester_set","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":"e2ec08ac02d66882"}},{"code_sha256_prefix":"569567299c57a97c","entry":"dist","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/kernels.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/kernels.py","link_basis":"harvester_set","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":"569567299c57a97c"}},{"code_sha256_prefix":"31352f1d9134ca1b","entry":"inverse","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/misc.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/misc.py","link_basis":"harvester_set","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":"31352f1d9134ca1b"}},{"code_sha256_prefix":"9ba9ae60d283b6b8","entry":"regularize_covariance","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"src/misc.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/src/misc.py","link_basis":"harvester_set","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":"9ba9ae60d283b6b8"}},{"code_sha256_prefix":"856f4852848eb8c5","entry":"sliceplot_pred_mean","repo":"P-Mikkola/PPBO","repo_kind":"listed","path":"camphor_copper/plot_results.py","file_url":"https://github.com/P-Mikkola/PPBO/blob/HEAD/camphor_copper/plot_results.py","link_basis":"harvester_set","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":"856f4852848eb8c5"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}