{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:KVU2URTJ3ECQINYTBTWJURDJBW","short_pith_number":"pith:KVU2URTJ","canonical_record":{"source":{"id":"1301.3837","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:48:59Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"c339d99ff87955486f795456503a6618749f78a3e3e950b95a7c709e4f454561","abstract_canon_sha256":"467f22a188ea62346dc8710b6cbe497a4a7e384867f3278c04a2599989565981"},"schema_version":"1.0"},"canonical_sha256":"5569aa4669d9050437130cec9a44690d85d274fee07f6199e7d28956cb510d90","source":{"kind":"arxiv","id":"1301.3837","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3837","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3837v1","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3837","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"pith_short_12","alias_value":"KVU2URTJ3ECQ","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"KVU2URTJ3ECQINYT","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"KVU2URTJ","created_at":"2026-05-18T12:27:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:KVU2URTJ3ECQINYTBTWJURDJBW","target":"record","payload":{"canonical_record":{"source":{"id":"1301.3837","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:48:59Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"c339d99ff87955486f795456503a6618749f78a3e3e950b95a7c709e4f454561","abstract_canon_sha256":"467f22a188ea62346dc8710b6cbe497a4a7e384867f3278c04a2599989565981"},"schema_version":"1.0"},"canonical_sha256":"5569aa4669d9050437130cec9a44690d85d274fee07f6199e7d28956cb510d90","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:36:15.483756Z","signature_b64":"CVD3R6H9TnvyY0c19PWBW4oAAqywwXNGJYaOYRkJ+dtK1pIfeGCmPxG4tp0hl8yn4YnpfkhOnXZJCnN6LMk4BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5569aa4669d9050437130cec9a44690d85d274fee07f6199e7d28956cb510d90","last_reissued_at":"2026-05-18T03:36:15.483095Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:36:15.483095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.3837","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:36:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T8+KCCFjCS2T3hK3ayOunaVE/NoAMCgQ7m5ry+Hj38cnZjLE1GAe+tW6Rk3zD/Gp1v+kCVkipHMGDfJWeTa7Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T00:52:25.194541Z"},"content_sha256":"7b208346f9bfd744a91756f86943b3dc2330ae86afb737b1b49702957d7bb1b6","schema_version":"1.0","event_id":"sha256:7b208346f9bfd744a91756f86943b3dc2330ae86afb737b1b49702957d7bb1b6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:KVU2URTJ3ECQINYTBTWJURDJBW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dynamic Bayesian Multinets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Jeff A. Bilmes","submitted_at":"2013-01-16T15:48:59Z","abstract_excerpt":"In this work, dynamic Bayesian multinets are introduced where a Markov chain state at time t determines conditional independence patterns between random variables lying within a local time window surrounding t.  It is shown how information-theoretic criterion functions can be used to induce sparse, discriminative, and class-conditional network structures that yield an optimal approximation to the class posterior probability, and therefore are useful for the classification task.  Using a new structure learning heuristic, the resulting models are tested on a medium-vocabulary isolated-word speec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3837","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:36:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8TnxDWNsBjreWEfoCMaJbFoKVFv/4HSKUn0I5XrONPu6nMTs91vsN0D7Qo/N/561afR0fgZkwY66W9CQabT1Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T00:52:25.194921Z"},"content_sha256":"03ceaebaa85b0169849e50c0e3720b95fc698591eb9f5f085c1dcb730d720a46","schema_version":"1.0","event_id":"sha256:03ceaebaa85b0169849e50c0e3720b95fc698591eb9f5f085c1dcb730d720a46"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KVU2URTJ3ECQINYTBTWJURDJBW/bundle.json","state_url":"https://pith.science/pith/KVU2URTJ3ECQINYTBTWJURDJBW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KVU2URTJ3ECQINYTBTWJURDJBW/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-05T00:52:25Z","links":{"resolver":"https://pith.science/pith/KVU2URTJ3ECQINYTBTWJURDJBW","bundle":"https://pith.science/pith/KVU2URTJ3ECQINYTBTWJURDJBW/bundle.json","state":"https://pith.science/pith/KVU2URTJ3ECQINYTBTWJURDJBW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KVU2URTJ3ECQINYTBTWJURDJBW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:KVU2URTJ3ECQINYTBTWJURDJBW","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":"467f22a188ea62346dc8710b6cbe497a4a7e384867f3278c04a2599989565981","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:48:59Z","title_canon_sha256":"c339d99ff87955486f795456503a6618749f78a3e3e950b95a7c709e4f454561"},"schema_version":"1.0","source":{"id":"1301.3837","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3837","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3837v1","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3837","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"pith_short_12","alias_value":"KVU2URTJ3ECQ","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"KVU2URTJ3ECQINYT","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"KVU2URTJ","created_at":"2026-05-18T12:27:51Z"}],"graph_snapshots":[{"event_id":"sha256:03ceaebaa85b0169849e50c0e3720b95fc698591eb9f5f085c1dcb730d720a46","target":"graph","created_at":"2026-05-18T03:36:15Z","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":"In this work, dynamic Bayesian multinets are introduced where a Markov chain state at time t determines conditional independence patterns between random variables lying within a local time window surrounding t.  It is shown how information-theoretic criterion functions can be used to induce sparse, discriminative, and class-conditional network structures that yield an optimal approximation to the class posterior probability, and therefore are useful for the classification task.  Using a new structure learning heuristic, the resulting models are tested on a medium-vocabulary isolated-word speec","authors_text":"Jeff A. Bilmes","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:48:59Z","title":"Dynamic Bayesian Multinets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3837","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":"sha256:7b208346f9bfd744a91756f86943b3dc2330ae86afb737b1b49702957d7bb1b6","target":"record","created_at":"2026-05-18T03:36:15Z","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":"467f22a188ea62346dc8710b6cbe497a4a7e384867f3278c04a2599989565981","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:48:59Z","title_canon_sha256":"c339d99ff87955486f795456503a6618749f78a3e3e950b95a7c709e4f454561"},"schema_version":"1.0","source":{"id":"1301.3837","kind":"arxiv","version":1}},"canonical_sha256":"5569aa4669d9050437130cec9a44690d85d274fee07f6199e7d28956cb510d90","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5569aa4669d9050437130cec9a44690d85d274fee07f6199e7d28956cb510d90","first_computed_at":"2026-05-18T03:36:15.483095Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:36:15.483095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CVD3R6H9TnvyY0c19PWBW4oAAqywwXNGJYaOYRkJ+dtK1pIfeGCmPxG4tp0hl8yn4YnpfkhOnXZJCnN6LMk4BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T03:36:15.483756Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.3837","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b208346f9bfd744a91756f86943b3dc2330ae86afb737b1b49702957d7bb1b6","sha256:03ceaebaa85b0169849e50c0e3720b95fc698591eb9f5f085c1dcb730d720a46"],"state_sha256":"90a59ea6d884605d5acd8aaeec39b370949dc24b79378fbd90d807441648ce33"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IvR1R6Omlk38r2hfm2TstLnyUODy1aSralgLwZ4xkpKUYoWA7DHrHK/8R/KxOOQM1qaVIzYiNeZKbj/5XNXNDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T00:52:25.196908Z","bundle_sha256":"b89bd88993397daac2d19747505cb2e566872107d0fdbd692d5f6273e43b9b94"}}