{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:MCNUKY6U5P2NDK4C4KCTODSN2J","short_pith_number":"pith:MCNUKY6U","schema_version":"1.0","canonical_sha256":"609b4563d4ebf4d1ab82e285370e4dd26f45caedc5546eff7d4aae814aa09d0d","source":{"kind":"arxiv","id":"2009.09259","version":1},"attestation_state":"computed","paper":{"title":"Bid Shading by Win-Rate Estimation and Surplus Maximization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.LG","stat.ML"],"primary_cat":"cs.GT","authors_text":"Aaron Flores, Bharatbhushan Shetty, Brendan Kitts, Djordje Gligorijevic, Hao He, Jianlong Zhang, Junwei Pan, San Gultekin, Shengjun Pan, Tian Zhou, Tingyu Mao","submitted_at":"2020-09-19T15:46:54Z","abstract_excerpt":"This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modified logistic regression to predict the profit from each possible shaded bid price. The function form allows fast maximization at run-time, a key requirement for Real-Time Bidding (RTB) systems. We report production results from this method along with several other algorithms. We found that bid shading, in general, can deliver significant value to advertisers, reducing price per impression to about 55% of the unshaded "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2009.09259","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2020-09-19T15:46:54Z","cross_cats_sorted":["cs.IR","cs.LG","stat.ML"],"title_canon_sha256":"75756bf61241bbf2cfadf14c24cc3c867621d5f28b5759ef4247bfa5f376fcb7","abstract_canon_sha256":"c23abef732caac5b9fc9e103398717db649daadeafee6d13d0e99bb387760441"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:36:35.844405Z","signature_b64":"kNAT7AgvxwDufkGyzQ2qkYjDrXsZG2fPCpNv0YdOD8t5i0GTwmA1Psz+sOGA3cZ/IYkfQK3HnfY0LlIxvqjbBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"609b4563d4ebf4d1ab82e285370e4dd26f45caedc5546eff7d4aae814aa09d0d","last_reissued_at":"2026-07-05T01:36:35.843958Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:36:35.843958Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bid Shading by Win-Rate Estimation and Surplus Maximization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR","cs.LG","stat.ML"],"primary_cat":"cs.GT","authors_text":"Aaron Flores, Bharatbhushan Shetty, Brendan Kitts, Djordje Gligorijevic, Hao He, Jianlong Zhang, Junwei Pan, San Gultekin, Shengjun Pan, Tian Zhou, Tingyu Mao","submitted_at":"2020-09-19T15:46:54Z","abstract_excerpt":"This paper describes a new win-rate based bid shading algorithm (WR) that does not rely on the minimum-bid-to-win feedback from a Sell-Side Platform (SSP). The method uses a modified logistic regression to predict the profit from each possible shaded bid price. The function form allows fast maximization at run-time, a key requirement for Real-Time Bidding (RTB) systems. We report production results from this method along with several other algorithms. We found that bid shading, in general, can deliver significant value to advertisers, reducing price per impression to about 55% of the unshaded "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.09259","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2009.09259/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2009.09259","created_at":"2026-07-05T01:36:35.844020+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.09259v1","created_at":"2026-07-05T01:36:35.844020+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.09259","created_at":"2026-07-05T01:36:35.844020+00:00"},{"alias_kind":"pith_short_12","alias_value":"MCNUKY6U5P2N","created_at":"2026-07-05T01:36:35.844020+00:00"},{"alias_kind":"pith_short_16","alias_value":"MCNUKY6U5P2NDK4C","created_at":"2026-07-05T01:36:35.844020+00:00"},{"alias_kind":"pith_short_8","alias_value":"MCNUKY6U","created_at":"2026-07-05T01:36:35.844020+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2508.06550","citing_title":"Generative Bid Shading in Real-Time Bidding Advertising","ref_index":23,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J","json":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J.json","graph_json":"https://pith.science/api/pith-number/MCNUKY6U5P2NDK4C4KCTODSN2J/graph.json","events_json":"https://pith.science/api/pith-number/MCNUKY6U5P2NDK4C4KCTODSN2J/events.json","paper":"https://pith.science/paper/MCNUKY6U"},"agent_actions":{"view_html":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J","download_json":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J.json","view_paper":"https://pith.science/paper/MCNUKY6U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.09259&json=true","fetch_graph":"https://pith.science/api/pith-number/MCNUKY6U5P2NDK4C4KCTODSN2J/graph.json","fetch_events":"https://pith.science/api/pith-number/MCNUKY6U5P2NDK4C4KCTODSN2J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J/action/storage_attestation","attest_author":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J/action/author_attestation","sign_citation":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J/action/citation_signature","submit_replication":"https://pith.science/pith/MCNUKY6U5P2NDK4C4KCTODSN2J/action/replication_record"}},"created_at":"2026-07-05T01:36:35.844020+00:00","updated_at":"2026-07-05T01:36:35.844020+00:00"}