{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:H7QNSIJIUELJYDULFT3LHMLGVD","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":"af0107f4039e9e6eabe245419e4547cc631fb088243712e636a3c5afd6c6cb6e","cross_cats_sorted":["cs.DC","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-01-17T08:51:11Z","title_canon_sha256":"26a534d9db54e40b69729e9ed0b60381c06fa45f963624ee66610350aaf5bee8"},"schema_version":"1.0","source":{"id":"2001.06194","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2001.06194","created_at":"2026-07-05T01:26:50Z"},{"alias_kind":"arxiv_version","alias_value":"2001.06194v2","created_at":"2026-07-05T01:26:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2001.06194","created_at":"2026-07-05T01:26:50Z"},{"alias_kind":"pith_short_12","alias_value":"H7QNSIJIUELJ","created_at":"2026-07-05T01:26:50Z"},{"alias_kind":"pith_short_16","alias_value":"H7QNSIJIUELJYDUL","created_at":"2026-07-05T01:26:50Z"},{"alias_kind":"pith_short_8","alias_value":"H7QNSIJI","created_at":"2026-07-05T01:26:50Z"}],"graph_snapshots":[{"event_id":"sha256:edbde1d9da6ebb2afaea5f54bc0b13f1eeebd8c0ef868620004e93b3fd1b7d92","target":"graph","created_at":"2026-07-05T01:26:50Z","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/2001.06194/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed statistical inference has recently attracted immense attention. The asymptotic efficiency of the maximum likelihood estimator (MLE), the one-step MLE, and the aggregated estimating equation estimator are established for generalized linear models under the \"large $n$, diverging $p_n$\" framework, where the dimension of the covariates $p_n$ grows to infinity at a polynomial rate $o(n^\\alpha)$ for some $0<\\alpha<1$. Then a novel method is proposed to obtain an asymptotically efficient estimator for large-scale distributed data by two rounds of communication. In this novel method, the a","authors_text":"Jingyi Ma, Maozai Tian, Ping Zhou, Ye Fan, Zhen Yu","cross_cats":["cs.DC","cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-01-17T08:51:11Z","title":"Communication-Efficient Distributed Estimator for Generalized Linear Models with a Diverging Number of Covariates"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2001.06194","kind":"arxiv","version":2},"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":"sha256:0153d583dd727edbce5084c0ec1e0efbe00f440c935d4c05de71b1d1d420a685","target":"record","created_at":"2026-07-05T01:26:50Z","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":"af0107f4039e9e6eabe245419e4547cc631fb088243712e636a3c5afd6c6cb6e","cross_cats_sorted":["cs.DC","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2020-01-17T08:51:11Z","title_canon_sha256":"26a534d9db54e40b69729e9ed0b60381c06fa45f963624ee66610350aaf5bee8"},"schema_version":"1.0","source":{"id":"2001.06194","kind":"arxiv","version":2}},"canonical_sha256":"3fe0d92128a1169c0e8b2cf6b3b166a8f7ccabdf9c0188edf268f79539f877df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3fe0d92128a1169c0e8b2cf6b3b166a8f7ccabdf9c0188edf268f79539f877df","first_computed_at":"2026-07-05T01:26:50.477893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:26:50.477893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Tdt1miVExe3gBheVI6YGfD7V9hess91HQIHi1Y4i1aTIcmpfk06s05/FjMka+oYbvy63OcsxnxO3TeDTJ5KSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:26:50.478339Z","signed_message":"canonical_sha256_bytes"},"source_id":"2001.06194","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0153d583dd727edbce5084c0ec1e0efbe00f440c935d4c05de71b1d1d420a685","sha256:edbde1d9da6ebb2afaea5f54bc0b13f1eeebd8c0ef868620004e93b3fd1b7d92"],"state_sha256":"f4948c69e9b4ae00a088cb55a368371a25ede84dda07a0f68ffd414d989179c0"}