{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:MHU5E4WWR4OXROWLYUPGAO3XH4","short_pith_number":"pith:MHU5E4WW","canonical_record":{"source":{"id":"1304.6803","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-04-25T05:37:55Z","cross_cats_sorted":[],"title_canon_sha256":"fcc2122e29bdbb00487607d696d07f6d8ecc3b7aa15482bead459608c277615a","abstract_canon_sha256":"614c49a2750ed8ba1595a5a3262fa4cda3f3610aa71fb02bb95eabdeca1ff99d"},"schema_version":"1.0"},"canonical_sha256":"61e9d272d68f1d78bacbc51e603b773f1f4db3df3a12c091a8edb555de743e16","source":{"kind":"arxiv","id":"1304.6803","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1304.6803","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"arxiv_version","alias_value":"1304.6803v5","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.6803","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"pith_short_12","alias_value":"MHU5E4WWR4OX","created_at":"2026-05-18T12:27:52Z"},{"alias_kind":"pith_short_16","alias_value":"MHU5E4WWR4OXROWL","created_at":"2026-05-18T12:27:52Z"},{"alias_kind":"pith_short_8","alias_value":"MHU5E4WW","created_at":"2026-05-18T12:27:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:MHU5E4WWR4OXROWLYUPGAO3XH4","target":"record","payload":{"canonical_record":{"source":{"id":"1304.6803","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-04-25T05:37:55Z","cross_cats_sorted":[],"title_canon_sha256":"fcc2122e29bdbb00487607d696d07f6d8ecc3b7aa15482bead459608c277615a","abstract_canon_sha256":"614c49a2750ed8ba1595a5a3262fa4cda3f3610aa71fb02bb95eabdeca1ff99d"},"schema_version":"1.0"},"canonical_sha256":"61e9d272d68f1d78bacbc51e603b773f1f4db3df3a12c091a8edb555de743e16","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:03:32.251779Z","signature_b64":"FZSkRJ6+g74tWoHID4jokIROp/+bU11fHvr4kLWvvaXRoYbBQnD9iLXOon7YBw4CwZYIcm9ScpUC4D+3BOM4AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61e9d272d68f1d78bacbc51e603b773f1f4db3df3a12c091a8edb555de743e16","last_reissued_at":"2026-05-18T03:03:32.251049Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:03:32.251049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1304.6803","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:03:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mFxFu41aXSqCZDOM12JyQ4lVhEmziWlBj99x3lRElkwMXmRU5XwmLIr9LbiaNYZ3GxS3KG2op7hUNyvAVzQ3BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T03:33:45.076007Z"},"content_sha256":"4047966ea5d8daabbeeb23ed8af7045ecbeb7c48bec487c1d7ae35d44acb5455","schema_version":"1.0","event_id":"sha256:4047966ea5d8daabbeeb23ed8af7045ecbeb7c48bec487c1d7ae35d44acb5455"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:MHU5E4WWR4OXROWLYUPGAO3XH4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"John A. Quinn, Masashi Sugiyama, Michael U. Gutmann, Song Liu, Taiji Suzuki","submitted_at":"2013-04-25T05:37:55Z","abstract_excerpt":"We propose a new method for detecting changes in Markov network structure between two sets of samples. Instead of naively fitting two Markov network models separately to the two data sets and figuring out their difference, we \\emph{directly} learn the network structure change by estimating the ratio of Markov network models. This density-ratio formulation naturally allows us to introduce sparsity in the network structure change, which highly contributes to enhancing interpretability. Furthermore, computation of the normalization term, which is a critical bottleneck of the naive approach, can b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.6803","kind":"arxiv","version":5},"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":"2026-05-18T03:03:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vhysWZnUiJoGoAABkAMXLPpNxWCbv4JDpS8+fQaXESgSCxmZ+iydI3zDzG30CuaQgxtusHA6KnWtnxpv4oZUAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T03:33:45.076712Z"},"content_sha256":"08385d54dcf8eaf3c630fa3da9d60d3e9195e5e67bcd41236fc8ed1ffbcbcc9c","schema_version":"1.0","event_id":"sha256:08385d54dcf8eaf3c630fa3da9d60d3e9195e5e67bcd41236fc8ed1ffbcbcc9c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/bundle.json","state_url":"https://pith.science/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/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":"2026-06-11T03:33:45Z","links":{"resolver":"https://pith.science/pith/MHU5E4WWR4OXROWLYUPGAO3XH4","bundle":"https://pith.science/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/bundle.json","state":"https://pith.science/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MHU5E4WWR4OXROWLYUPGAO3XH4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:MHU5E4WWR4OXROWLYUPGAO3XH4","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":"614c49a2750ed8ba1595a5a3262fa4cda3f3610aa71fb02bb95eabdeca1ff99d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-04-25T05:37:55Z","title_canon_sha256":"fcc2122e29bdbb00487607d696d07f6d8ecc3b7aa15482bead459608c277615a"},"schema_version":"1.0","source":{"id":"1304.6803","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1304.6803","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"arxiv_version","alias_value":"1304.6803v5","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.6803","created_at":"2026-05-18T03:03:32Z"},{"alias_kind":"pith_short_12","alias_value":"MHU5E4WWR4OX","created_at":"2026-05-18T12:27:52Z"},{"alias_kind":"pith_short_16","alias_value":"MHU5E4WWR4OXROWL","created_at":"2026-05-18T12:27:52Z"},{"alias_kind":"pith_short_8","alias_value":"MHU5E4WW","created_at":"2026-05-18T12:27:52Z"}],"graph_snapshots":[{"event_id":"sha256:08385d54dcf8eaf3c630fa3da9d60d3e9195e5e67bcd41236fc8ed1ffbcbcc9c","target":"graph","created_at":"2026-05-18T03:03:32Z","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":"We propose a new method for detecting changes in Markov network structure between two sets of samples. Instead of naively fitting two Markov network models separately to the two data sets and figuring out their difference, we \\emph{directly} learn the network structure change by estimating the ratio of Markov network models. This density-ratio formulation naturally allows us to introduce sparsity in the network structure change, which highly contributes to enhancing interpretability. Furthermore, computation of the normalization term, which is a critical bottleneck of the naive approach, can b","authors_text":"John A. Quinn, Masashi Sugiyama, Michael U. Gutmann, Song Liu, Taiji Suzuki","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-04-25T05:37:55Z","title":"Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.6803","kind":"arxiv","version":5},"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":"sha256:4047966ea5d8daabbeeb23ed8af7045ecbeb7c48bec487c1d7ae35d44acb5455","target":"record","created_at":"2026-05-18T03:03:32Z","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":"614c49a2750ed8ba1595a5a3262fa4cda3f3610aa71fb02bb95eabdeca1ff99d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-04-25T05:37:55Z","title_canon_sha256":"fcc2122e29bdbb00487607d696d07f6d8ecc3b7aa15482bead459608c277615a"},"schema_version":"1.0","source":{"id":"1304.6803","kind":"arxiv","version":5}},"canonical_sha256":"61e9d272d68f1d78bacbc51e603b773f1f4db3df3a12c091a8edb555de743e16","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"61e9d272d68f1d78bacbc51e603b773f1f4db3df3a12c091a8edb555de743e16","first_computed_at":"2026-05-18T03:03:32.251049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:03:32.251049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FZSkRJ6+g74tWoHID4jokIROp/+bU11fHvr4kLWvvaXRoYbBQnD9iLXOon7YBw4CwZYIcm9ScpUC4D+3BOM4AA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:03:32.251779Z","signed_message":"canonical_sha256_bytes"},"source_id":"1304.6803","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4047966ea5d8daabbeeb23ed8af7045ecbeb7c48bec487c1d7ae35d44acb5455","sha256:08385d54dcf8eaf3c630fa3da9d60d3e9195e5e67bcd41236fc8ed1ffbcbcc9c"],"state_sha256":"296275f40def71de5fa955388561190624202d75d7459c19f3bed64a90796f53"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EpO0fMDo0GcQAYWN2OASGvsb4YX8KGO50iYJ4T3FKFHa/PXPgfS2qD/dNYLtkr4UCCt+Q0ajqtzYsnS2f3BiBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T03:33:45.080845Z","bundle_sha256":"c2c6ed693b4136e6a645d37783dec781fed1e3d426b62a942803fc4fc0365211"}}