{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:AZFUYHPCDIVIBEJO3IFSUVVYL3","short_pith_number":"pith:AZFUYHPC","canonical_record":{"source":{"id":"2012.15726","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2020-12-22T20:37:57Z","cross_cats_sorted":["cs.LG","stat.ME","stat.TH"],"title_canon_sha256":"505877ba66863632bb7364da007363fe7dbbe3a148749e2227845c7d5d47d095","abstract_canon_sha256":"411037fcbbfd88231ecd9dc8de9a18147482f79b3441f55d4e83664cbea44601"},"schema_version":"1.0"},"canonical_sha256":"064b4c1de21a2a80912eda0b2a56b85eea87044b59f5e453a8254d1b041499ab","source":{"kind":"arxiv","id":"2012.15726","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.15726","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"arxiv_version","alias_value":"2012.15726v1","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.15726","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_12","alias_value":"AZFUYHPCDIVI","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_16","alias_value":"AZFUYHPCDIVIBEJO","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_8","alias_value":"AZFUYHPC","created_at":"2026-07-05T02:03:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:AZFUYHPCDIVIBEJO3IFSUVVYL3","target":"record","payload":{"canonical_record":{"source":{"id":"2012.15726","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2020-12-22T20:37:57Z","cross_cats_sorted":["cs.LG","stat.ME","stat.TH"],"title_canon_sha256":"505877ba66863632bb7364da007363fe7dbbe3a148749e2227845c7d5d47d095","abstract_canon_sha256":"411037fcbbfd88231ecd9dc8de9a18147482f79b3441f55d4e83664cbea44601"},"schema_version":"1.0"},"canonical_sha256":"064b4c1de21a2a80912eda0b2a56b85eea87044b59f5e453a8254d1b041499ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:03:20.858679Z","signature_b64":"wUnTlryNrYjZAJ932/unHiuNM8YIuVG0eLJDXvMl70tNvJJSV8TwSlnqXqJp1ezy6ycm0Xgu2wfAiqX8zcDlAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"064b4c1de21a2a80912eda0b2a56b85eea87044b59f5e453a8254d1b041499ab","last_reissued_at":"2026-07-05T02:03:20.858285Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:03:20.858285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2012.15726","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:03:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e0kZGkv1imN3hrNwBnj9teepPdDpPDKyiXshodPxH9HlyE1EvNy8pjH0mvqLwDm3SSokOWiFgHoUel1JIW4qAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T07:23:21.559569Z"},"content_sha256":"e4078fb9136ffd9c191e44cdfa5625c2050db7803c3917257631ebe1bfdaddc2","schema_version":"1.0","event_id":"sha256:e4078fb9136ffd9c191e44cdfa5625c2050db7803c3917257631ebe1bfdaddc2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:AZFUYHPCDIVIBEJO3IFSUVVYL3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Refined bounds for randomized experimental design","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Albert Thomas, Geovani Rizk, Igor Colin, Moez Draief","submitted_at":"2020-12-22T20:37:57Z","abstract_excerpt":"Experimental design is an approach for selecting samples among a given set so as to obtain the best estimator for a given criterion. In the context of linear regression, several optimal designs have been derived, each associated with a different criterion: mean square error, robustness, \\emph{etc}. Computing such designs is generally an NP-hard problem and one can instead rely on a convex relaxation that considers probability distributions over the samples. Although greedy strategies and rounding procedures have received a lot of attention, straightforward sampling from the optimal distributio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.15726","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/2012.15726/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:03:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Sc3sktTiOCXMLG1thhDrPFTmIFQC0BRA2Yti2oYOrXwitL4rvEKMCY9YuRPi9FY8gdunw3TTLPQvR6i59DicBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T07:23:21.560061Z"},"content_sha256":"9f365dd800b7591860193fbad2caa2ff87d79c5fd47ac90bb1f13806ff81923e","schema_version":"1.0","event_id":"sha256:9f365dd800b7591860193fbad2caa2ff87d79c5fd47ac90bb1f13806ff81923e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/bundle.json","state_url":"https://pith.science/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T07:23:21Z","links":{"resolver":"https://pith.science/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3","bundle":"https://pith.science/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/bundle.json","state":"https://pith.science/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AZFUYHPCDIVIBEJO3IFSUVVYL3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:AZFUYHPCDIVIBEJO3IFSUVVYL3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"411037fcbbfd88231ecd9dc8de9a18147482f79b3441f55d4e83664cbea44601","cross_cats_sorted":["cs.LG","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2020-12-22T20:37:57Z","title_canon_sha256":"505877ba66863632bb7364da007363fe7dbbe3a148749e2227845c7d5d47d095"},"schema_version":"1.0","source":{"id":"2012.15726","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2012.15726","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"arxiv_version","alias_value":"2012.15726v1","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2012.15726","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_12","alias_value":"AZFUYHPCDIVI","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_16","alias_value":"AZFUYHPCDIVIBEJO","created_at":"2026-07-05T02:03:20Z"},{"alias_kind":"pith_short_8","alias_value":"AZFUYHPC","created_at":"2026-07-05T02:03:20Z"}],"graph_snapshots":[{"event_id":"sha256:9f365dd800b7591860193fbad2caa2ff87d79c5fd47ac90bb1f13806ff81923e","target":"graph","created_at":"2026-07-05T02:03:20Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2012.15726/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Experimental design is an approach for selecting samples among a given set so as to obtain the best estimator for a given criterion. In the context of linear regression, several optimal designs have been derived, each associated with a different criterion: mean square error, robustness, \\emph{etc}. Computing such designs is generally an NP-hard problem and one can instead rely on a convex relaxation that considers probability distributions over the samples. Although greedy strategies and rounding procedures have received a lot of attention, straightforward sampling from the optimal distributio","authors_text":"Albert Thomas, Geovani Rizk, Igor Colin, Moez Draief","cross_cats":["cs.LG","stat.ME","stat.TH"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2020-12-22T20:37:57Z","title":"Refined bounds for randomized experimental design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2012.15726","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:e4078fb9136ffd9c191e44cdfa5625c2050db7803c3917257631ebe1bfdaddc2","target":"record","created_at":"2026-07-05T02:03:20Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"411037fcbbfd88231ecd9dc8de9a18147482f79b3441f55d4e83664cbea44601","cross_cats_sorted":["cs.LG","stat.ME","stat.TH"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.ST","submitted_at":"2020-12-22T20:37:57Z","title_canon_sha256":"505877ba66863632bb7364da007363fe7dbbe3a148749e2227845c7d5d47d095"},"schema_version":"1.0","source":{"id":"2012.15726","kind":"arxiv","version":1}},"canonical_sha256":"064b4c1de21a2a80912eda0b2a56b85eea87044b59f5e453a8254d1b041499ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"064b4c1de21a2a80912eda0b2a56b85eea87044b59f5e453a8254d1b041499ab","first_computed_at":"2026-07-05T02:03:20.858285Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:03:20.858285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wUnTlryNrYjZAJ932/unHiuNM8YIuVG0eLJDXvMl70tNvJJSV8TwSlnqXqJp1ezy6ycm0Xgu2wfAiqX8zcDlAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:03:20.858679Z","signed_message":"canonical_sha256_bytes"},"source_id":"2012.15726","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4078fb9136ffd9c191e44cdfa5625c2050db7803c3917257631ebe1bfdaddc2","sha256:9f365dd800b7591860193fbad2caa2ff87d79c5fd47ac90bb1f13806ff81923e"],"state_sha256":"1affd08cf3ea1e96b044e623eeeaa2fff4fe4a90570fa7d20bae7b1f3f4f61b9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8vcgWKCC5ujnaqWi9O/b/D1NkVk8azvvBHm7b0oy7z8ftFra4cUE4nES/RV6qaQQUYMDbwmCk8rwbwv3hRw7Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T07:23:21.563703Z","bundle_sha256":"58c754cfe396b6e69f892f7511b2cc1bc7726bdacab0f21c3310cf37ca6f1899"}}