{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:3O6ZLCWA6Z3MDBQKQ6HA4AB5WX","short_pith_number":"pith:3O6ZLCWA","schema_version":"1.0","canonical_sha256":"dbbd958ac0f676c1860a878e0e003db5faa70e3fc0e389afab164d3d4bb58b2b","source":{"kind":"arxiv","id":"1801.07030","version":1},"attestation_state":"computed","paper":{"title":"Offline A/B testing for Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Alexandre Abraham, Alexandre Gilotte, Cl\\'ement Calauz\\`enes, Simon Doll\\'e, Thomas Nedelec","submitted_at":"2018-01-22T10:31:56Z","abstract_excerpt":"Before A/B testing online a new version of a recommender system, it is usual to perform some offline evaluations on historical data. We focus on evaluation methods that compute an estimator of the potential uplift in revenue that could generate this new technology. It helps to iterate faster and to avoid losing money by detecting poor policies. These estimators are known as counterfactual or off-policy estimators. We show that traditional counterfactual estimators such as capped importance sampling and normalised importance sampling are experimentally not having satisfying bias-variance compro"},"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":"1801.07030","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-01-22T10:31:56Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"14378b3cb8f90832f3687c947ce803f9c3154d78b1b60c555aee7727fe273e23","abstract_canon_sha256":"03f9aefed4fb9fb94bdb3113a62fc5f34ce0d2cc72191abfe053108d28cca70c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:22.439628Z","signature_b64":"07ghGzYpMccZzyuWngcsdjSX+TT49t2d4+ldGQtRUelFz+un1L52MiA2nwsMgOl9YQohGHOIES/HvjPNrsJvDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dbbd958ac0f676c1860a878e0e003db5faa70e3fc0e389afab164d3d4bb58b2b","last_reissued_at":"2026-05-18T00:25:22.438916Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:22.438916Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Offline A/B testing for Recommender Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Alexandre Abraham, Alexandre Gilotte, Cl\\'ement Calauz\\`enes, Simon Doll\\'e, Thomas Nedelec","submitted_at":"2018-01-22T10:31:56Z","abstract_excerpt":"Before A/B testing online a new version of a recommender system, it is usual to perform some offline evaluations on historical data. We focus on evaluation methods that compute an estimator of the potential uplift in revenue that could generate this new technology. It helps to iterate faster and to avoid losing money by detecting poor policies. These estimators are known as counterfactual or off-policy estimators. We show that traditional counterfactual estimators such as capped importance sampling and normalised importance sampling are experimentally not having satisfying bias-variance compro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.07030","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":""},"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":"1801.07030","created_at":"2026-05-18T00:25:22.439038+00:00"},{"alias_kind":"arxiv_version","alias_value":"1801.07030v1","created_at":"2026-05-18T00:25:22.439038+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.07030","created_at":"2026-05-18T00:25:22.439038+00:00"},{"alias_kind":"pith_short_12","alias_value":"3O6ZLCWA6Z3M","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_16","alias_value":"3O6ZLCWA6Z3MDBQK","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_8","alias_value":"3O6ZLCWA","created_at":"2026-05-18T12:32:02.567920+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX","json":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX.json","graph_json":"https://pith.science/api/pith-number/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/graph.json","events_json":"https://pith.science/api/pith-number/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/events.json","paper":"https://pith.science/paper/3O6ZLCWA"},"agent_actions":{"view_html":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX","download_json":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX.json","view_paper":"https://pith.science/paper/3O6ZLCWA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1801.07030&json=true","fetch_graph":"https://pith.science/api/pith-number/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/graph.json","fetch_events":"https://pith.science/api/pith-number/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/action/storage_attestation","attest_author":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/action/author_attestation","sign_citation":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/action/citation_signature","submit_replication":"https://pith.science/pith/3O6ZLCWA6Z3MDBQKQ6HA4AB5WX/action/replication_record"}},"created_at":"2026-05-18T00:25:22.439038+00:00","updated_at":"2026-05-18T00:25:22.439038+00:00"}