{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PDZAJAYBK24XHZ2XQCHR5252SS","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":"eac67d30ca53560c24d0cea07b354828b44c4bf458668109889b0a265e7ee489","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-03-09T14:32:21Z","title_canon_sha256":"a3de67cb1bad5c26830dc2329bab49860af11b79cdfec0d29f403a3dc3bbae98"},"schema_version":"1.0","source":{"id":"1903.03810","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.03810","created_at":"2026-05-17T23:51:40Z"},{"alias_kind":"arxiv_version","alias_value":"1903.03810v1","created_at":"2026-05-17T23:51:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.03810","created_at":"2026-05-17T23:51:40Z"},{"alias_kind":"pith_short_12","alias_value":"PDZAJAYBK24X","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PDZAJAYBK24XHZ2X","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PDZAJAYB","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:ee9e5e20cdbddbf3432ea5f23c7612cf70b4cbd1270d3d7d013617fe2af13d59","target":"graph","created_at":"2026-05-17T23:51:40Z","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"},"paper":{"abstract_excerpt":"Feature screening is a powerful tool in the analysis of high dimensional data. When the sample size $N$ and the number of features $p$ are both large, the implementation of classic screening methods can be numerically challenging. In this paper, we propose a distributed screening framework for big data setup. In the spirit of \"divide-and-conquer\", the proposed framework expresses a correlation measure as a function of several component parameters, each of which can be distributively estimated using a natural U-statistic from data segments. With the component estimates aggregated, we obtain a f","authors_text":"Chen Xu, Runze Li, Xingxiang Li, Zhiming Xia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-03-09T14:32:21Z","title":"Distributed Feature Screening via Componentwise Debiasing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.03810","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":"sha256:9628f27bc2ec73a67a59a72a240e2d85aa5f9a17f7b2776284a8bed3607f2841","target":"record","created_at":"2026-05-17T23:51:40Z","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":"eac67d30ca53560c24d0cea07b354828b44c4bf458668109889b0a265e7ee489","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2019-03-09T14:32:21Z","title_canon_sha256":"a3de67cb1bad5c26830dc2329bab49860af11b79cdfec0d29f403a3dc3bbae98"},"schema_version":"1.0","source":{"id":"1903.03810","kind":"arxiv","version":1}},"canonical_sha256":"78f204830156b973e757808f1eebba9487f219f25fdb5e3032c01645583d5414","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"78f204830156b973e757808f1eebba9487f219f25fdb5e3032c01645583d5414","first_computed_at":"2026-05-17T23:51:40.888130Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:40.888130Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nHnm7yOKKO5Coyk8O7LtJVYz+D3wTvBlGsTVHj6USUJGjxbfye/dTggkTiVTZIDajhN41WfdsfOjClBbm2QkAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:40.888717Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.03810","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9628f27bc2ec73a67a59a72a240e2d85aa5f9a17f7b2776284a8bed3607f2841","sha256:ee9e5e20cdbddbf3432ea5f23c7612cf70b4cbd1270d3d7d013617fe2af13d59"],"state_sha256":"e1f2922a37f5d6182621be8d937ca5443817adca4002ed7e9f8cab1b48d5954d"}