{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:BXCVFIAWPE4GTSTJXBJ55OJROT","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":"8e679015990862d4c69e9c3c72018cd3683f189dcc74d8e39a213e7ab47406fe","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2011-10-12T12:17:51Z","title_canon_sha256":"c788cbe0b540efdba743d26fbea8a6080651a7d09ec9989d2aa7752af7b979ce"},"schema_version":"1.0","source":{"id":"1110.3239","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1110.3239","created_at":"2026-05-18T02:21:35Z"},{"alias_kind":"arxiv_version","alias_value":"1110.3239v1","created_at":"2026-05-18T02:21:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1110.3239","created_at":"2026-05-18T02:21:35Z"},{"alias_kind":"pith_short_12","alias_value":"BXCVFIAWPE4G","created_at":"2026-05-18T12:26:24Z"},{"alias_kind":"pith_short_16","alias_value":"BXCVFIAWPE4GTSTJ","created_at":"2026-05-18T12:26:24Z"},{"alias_kind":"pith_short_8","alias_value":"BXCVFIAW","created_at":"2026-05-18T12:26:24Z"}],"graph_snapshots":[{"event_id":"sha256:e2e8252342cd82db521c10aef8dd6ae0232ff43c0f83d2b6bdc3ba6231d72cb2","target":"graph","created_at":"2026-05-18T02:21:35Z","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":"This paper addresses the estimation of parameters of a Bayesian network from incomplete data. The task is usually tackled by running the Expectation-Maximization (EM) algorithm several times in order to obtain a high log-likelihood estimate. We argue that choosing the maximum log-likelihood estimate (as well as the maximum penalized log-likelihood and the maximum a posteriori estimate) has severe drawbacks, being affected both by overfitting and model uncertainty. Two ideas are discussed to overcome these issues: a maximum entropy approach and a Bayesian model averaging approach. Both ideas ca","authors_text":"Cassio P. de Campos, Giorgio Corani","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2011-10-12T12:17:51Z","title":"Improving parameter learning of Bayesian nets from incomplete data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1110.3239","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":"sha256:566dfcf5a1926607fae8c00376a4c02b1df5186411ddcce443c20dad4179c5c9","target":"record","created_at":"2026-05-18T02:21:35Z","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":"8e679015990862d4c69e9c3c72018cd3683f189dcc74d8e39a213e7ab47406fe","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2011-10-12T12:17:51Z","title_canon_sha256":"c788cbe0b540efdba743d26fbea8a6080651a7d09ec9989d2aa7752af7b979ce"},"schema_version":"1.0","source":{"id":"1110.3239","kind":"arxiv","version":1}},"canonical_sha256":"0dc552a016793869ca69b853deb93174d9a5f43058407d95ce0e5be998c5c00a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0dc552a016793869ca69b853deb93174d9a5f43058407d95ce0e5be998c5c00a","first_computed_at":"2026-05-18T02:21:35.275999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:21:35.275999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TBi7bauC+4WgTH2ROcTrDqkWATckdSaeRW0wdH2yE8vHHVuR8z2awdZZricXX2K7ngQ0UwKEfmSvK63aWOMgDA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:21:35.276498Z","signed_message":"canonical_sha256_bytes"},"source_id":"1110.3239","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:566dfcf5a1926607fae8c00376a4c02b1df5186411ddcce443c20dad4179c5c9","sha256:e2e8252342cd82db521c10aef8dd6ae0232ff43c0f83d2b6bdc3ba6231d72cb2"],"state_sha256":"861f6e97531761b6c521d5efe0bd45153e2979482a6da9100d0f6fb42843ce25"}