{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:SU74QSB4TZCBUFZU6GZUQLGPUE","short_pith_number":"pith:SU74QSB4","schema_version":"1.0","canonical_sha256":"953fc8483c9e441a1734f1b3482ccfa1276e6d54a7467809088c3d22e582030b","source":{"kind":"arxiv","id":"1307.8430","version":1},"attestation_state":"computed","paper":{"title":"Fast Simultaneous Training of Generalized Linear Models (FaSTGLZ)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Brian Cheung, Bryan R. Conroy, Jennifer M. Walz, Paul Sajda","submitted_at":"2013-07-31T19:18:11Z","abstract_excerpt":"We present an efficient algorithm for simultaneously training sparse generalized linear models across many related problems, which may arise from bootstrapping, cross-validation and nonparametric permutation testing. Our approach leverages the redundancies across problems to obtain significant computational improvements relative to solving the problems sequentially by a conventional algorithm. We demonstrate our fast simultaneous training of generalized linear models (FaSTGLZ) algorithm on a number of real-world datasets, and we run otherwise computationally intensive bootstrapping and permuta"},"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":"1307.8430","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-07-31T19:18:11Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"43529dabe049cb9bfc40246bb328685de76eeae8a6c6d30b7b6bb39d8f9f5782","abstract_canon_sha256":"ec9a7fe1d209e84febc128715702927aba780216edf1e114ae7f276e43f7c726"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:17:01.165946Z","signature_b64":"GQqLl3KsM5ti0Kr3w3XWeVtjDoy7/OhgWnj0vEoLij/cxahKl0XQBmUBLKzj6Sx/yA4EJkY2VWa08KsaS29GBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"953fc8483c9e441a1734f1b3482ccfa1276e6d54a7467809088c3d22e582030b","last_reissued_at":"2026-05-18T03:17:01.165188Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:17:01.165188Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast Simultaneous Training of Generalized Linear Models (FaSTGLZ)","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Brian Cheung, Bryan R. Conroy, Jennifer M. Walz, Paul Sajda","submitted_at":"2013-07-31T19:18:11Z","abstract_excerpt":"We present an efficient algorithm for simultaneously training sparse generalized linear models across many related problems, which may arise from bootstrapping, cross-validation and nonparametric permutation testing. Our approach leverages the redundancies across problems to obtain significant computational improvements relative to solving the problems sequentially by a conventional algorithm. We demonstrate our fast simultaneous training of generalized linear models (FaSTGLZ) algorithm on a number of real-world datasets, and we run otherwise computationally intensive bootstrapping and permuta"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1307.8430","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":"1307.8430","created_at":"2026-05-18T03:17:01.165293+00:00"},{"alias_kind":"arxiv_version","alias_value":"1307.8430v1","created_at":"2026-05-18T03:17:01.165293+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1307.8430","created_at":"2026-05-18T03:17:01.165293+00:00"},{"alias_kind":"pith_short_12","alias_value":"SU74QSB4TZCB","created_at":"2026-05-18T12:27:59.945178+00:00"},{"alias_kind":"pith_short_16","alias_value":"SU74QSB4TZCBUFZU","created_at":"2026-05-18T12:27:59.945178+00:00"},{"alias_kind":"pith_short_8","alias_value":"SU74QSB4","created_at":"2026-05-18T12:27:59.945178+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/SU74QSB4TZCBUFZU6GZUQLGPUE","json":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE.json","graph_json":"https://pith.science/api/pith-number/SU74QSB4TZCBUFZU6GZUQLGPUE/graph.json","events_json":"https://pith.science/api/pith-number/SU74QSB4TZCBUFZU6GZUQLGPUE/events.json","paper":"https://pith.science/paper/SU74QSB4"},"agent_actions":{"view_html":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE","download_json":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE.json","view_paper":"https://pith.science/paper/SU74QSB4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1307.8430&json=true","fetch_graph":"https://pith.science/api/pith-number/SU74QSB4TZCBUFZU6GZUQLGPUE/graph.json","fetch_events":"https://pith.science/api/pith-number/SU74QSB4TZCBUFZU6GZUQLGPUE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE/action/storage_attestation","attest_author":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE/action/author_attestation","sign_citation":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE/action/citation_signature","submit_replication":"https://pith.science/pith/SU74QSB4TZCBUFZU6GZUQLGPUE/action/replication_record"}},"created_at":"2026-05-18T03:17:01.165293+00:00","updated_at":"2026-05-18T03:17:01.165293+00:00"}