{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:JRXYPNJ4PRIUZRUPYHLU3X5IZ5","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":"51f496f2fe689819b649141f03a728aa5cf3884951f862840b708c73a2f00dd3","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-09-08T07:47:56Z","title_canon_sha256":"0f1bc663ec29315d47d95be6b6268772271012848764c9a354745d89561d7c89"},"schema_version":"1.0","source":{"id":"2209.03617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.03617","created_at":"2026-07-05T04:55:44Z"},{"alias_kind":"arxiv_version","alias_value":"2209.03617v1","created_at":"2026-07-05T04:55:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.03617","created_at":"2026-07-05T04:55:44Z"},{"alias_kind":"pith_short_12","alias_value":"JRXYPNJ4PRIU","created_at":"2026-07-05T04:55:44Z"},{"alias_kind":"pith_short_16","alias_value":"JRXYPNJ4PRIUZRUP","created_at":"2026-07-05T04:55:44Z"},{"alias_kind":"pith_short_8","alias_value":"JRXYPNJ4","created_at":"2026-07-05T04:55:44Z"}],"graph_snapshots":[{"event_id":"sha256:8ffa8139a301dac1490b26e63e1b46b39115da828ca29266425cf2959bb6372b","target":"graph","created_at":"2026-07-05T04:55:44Z","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/2209.03617/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Subsampling or subdata selection is a useful approach in large-scale statistical learning. Most existing studies focus on model-based subsampling methods which significantly depend on the model assumption. In this paper, we consider the model-free subsampling strategy for generating subdata from the original full data. In order to measure the goodness of representation of a subdata with respect to the original data, we propose a criterion, generalized empirical F-discrepancy (GEFD), and study its theoretical properties in connection with the classical generalized L2-discrepancy in the theory o","authors_text":"Aijun Zhang, Mei Zhang, Yongdao Zhou, Zheng Zhou","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-09-08T07:47:56Z","title":"Model-free Subsampling Method Based on Uniform Designs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.03617","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:b59724a1d101083979edb0ac492cc50596f53283f3eac735265e26a5912aee33","target":"record","created_at":"2026-07-05T04:55:44Z","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":"51f496f2fe689819b649141f03a728aa5cf3884951f862840b708c73a2f00dd3","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ME","submitted_at":"2022-09-08T07:47:56Z","title_canon_sha256":"0f1bc663ec29315d47d95be6b6268772271012848764c9a354745d89561d7c89"},"schema_version":"1.0","source":{"id":"2209.03617","kind":"arxiv","version":1}},"canonical_sha256":"4c6f87b53c7c514cc68fc1d74ddfa8cf5cf2c6f901c4c4627dbd6fa3929391af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c6f87b53c7c514cc68fc1d74ddfa8cf5cf2c6f901c4c4627dbd6fa3929391af","first_computed_at":"2026-07-05T04:55:44.025580Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:55:44.025580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zFXNU0D0u5IV9jzNrPpZavaxMzlniNH7K36v1fZZy21vnSDwDYnapyb0mRI/W7Orev90QTxGvEseI96EzQrRBw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:55:44.025932Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.03617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b59724a1d101083979edb0ac492cc50596f53283f3eac735265e26a5912aee33","sha256:8ffa8139a301dac1490b26e63e1b46b39115da828ca29266425cf2959bb6372b"],"state_sha256":"804a98d1d0883b093dea41f38e50465381854702c08a792980d3f20bbafc3206"}