{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:62UPGVFQUC6BNNTRLKOPMRWKGQ","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":"c3ed882fe72515ebc5c5e3247e6533959c7afa7a9e270e1b1ddcd07e479b184c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-08T23:50:19Z","title_canon_sha256":"4ea7e961afc761c812f3bbeb6de214540edec0cab29d071c6ea2ea28e7f5b159"},"schema_version":"1.0","source":{"id":"1703.03074","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.03074","created_at":"2026-05-18T00:02:36Z"},{"alias_kind":"arxiv_version","alias_value":"1703.03074v4","created_at":"2026-05-18T00:02:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.03074","created_at":"2026-05-18T00:02:36Z"},{"alias_kind":"pith_short_12","alias_value":"62UPGVFQUC6B","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"62UPGVFQUC6BNNTR","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"62UPGVFQ","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:8ee96446c50b7e6b425f3609ba4542afb0ca3d77b0d408dce957ed5c3998fffb","target":"graph","created_at":"2026-05-18T00:02:36Z","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":"Structural learning of Bayesian Networks (BNs) is a NP-hard problem, which is further complicated by many theoretical issues, such as the I-equivalence among different structures. In this work, we focus on a specific subclass of BNs, named Suppes-Bayes Causal Networks (SBCNs), which include specific structural constraints based on Suppes' probabilistic causation to efficiently model cumulative phenomena. Here we compare the performance, via extensive simulations, of various state-of-the-art search strategies, such as local search techniques and Genetic Algorithms, as well as of distinct regula","authors_text":"Alex Graudenzi, Daniele Ramazzotti, Marco Antoniotti, Marco S. Nobile","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-08T23:50:19Z","title":"Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.03074","kind":"arxiv","version":4},"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":"sha256:57dcf29aee9b156f25fe2ee4aa3b8ed70a6c6352687b1b2e549459647a239971","target":"record","created_at":"2026-05-18T00:02:36Z","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":"c3ed882fe72515ebc5c5e3247e6533959c7afa7a9e270e1b1ddcd07e479b184c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-08T23:50:19Z","title_canon_sha256":"4ea7e961afc761c812f3bbeb6de214540edec0cab29d071c6ea2ea28e7f5b159"},"schema_version":"1.0","source":{"id":"1703.03074","kind":"arxiv","version":4}},"canonical_sha256":"f6a8f354b0a0bc16b6715a9cf646ca343a4ae0c3f39b3ce34e4892694c28fe45","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f6a8f354b0a0bc16b6715a9cf646ca343a4ae0c3f39b3ce34e4892694c28fe45","first_computed_at":"2026-05-18T00:02:36.501345Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:36.501345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8Ar2z9H7RFaMTpEs4a7UQqPlu6HeI/iEHMVu9eb3+qGlxhlR0n8gEUSIFbbN1/l5JvZ++1jd3uisYs7mSmzXAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:36.502045Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.03074","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:57dcf29aee9b156f25fe2ee4aa3b8ed70a6c6352687b1b2e549459647a239971","sha256:8ee96446c50b7e6b425f3609ba4542afb0ca3d77b0d408dce957ed5c3998fffb"],"state_sha256":"a2619579f5c44b76154ed19fe4fb4ff51bb216e8430dce4b799c3d99ddb6431a"}