{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:UN7UQ7H5MPIUVOGY5Q7K4XCLLF","short_pith_number":"pith:UN7UQ7H5","canonical_record":{"source":{"id":"1904.09792","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2019-04-22T10:19:58Z","cross_cats_sorted":["cs.LG","cs.SI","math.OC"],"title_canon_sha256":"456ebb04df67d8b3484ebf5b5bad33ec641261494b404190c354eb79aa5d41bc","abstract_canon_sha256":"24da5ffab58d60f42481ce32de9b77ae8dfb981d22db1e694e35d7a9c8464162"},"schema_version":"1.0"},"canonical_sha256":"a37f487cfd63d14ab8d8ec3eae5c4b595def1f44dfcfb5cb308c50562fd0ee0a","source":{"kind":"arxiv","id":"1904.09792","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.09792","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"arxiv_version","alias_value":"1904.09792v1","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.09792","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"pith_short_12","alias_value":"UN7UQ7H5MPIU","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"UN7UQ7H5MPIUVOGY","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"UN7UQ7H5","created_at":"2026-05-18T12:33:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:UN7UQ7H5MPIUVOGY5Q7K4XCLLF","target":"record","payload":{"canonical_record":{"source":{"id":"1904.09792","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2019-04-22T10:19:58Z","cross_cats_sorted":["cs.LG","cs.SI","math.OC"],"title_canon_sha256":"456ebb04df67d8b3484ebf5b5bad33ec641261494b404190c354eb79aa5d41bc","abstract_canon_sha256":"24da5ffab58d60f42481ce32de9b77ae8dfb981d22db1e694e35d7a9c8464162"},"schema_version":"1.0"},"canonical_sha256":"a37f487cfd63d14ab8d8ec3eae5c4b595def1f44dfcfb5cb308c50562fd0ee0a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:03.313118Z","signature_b64":"bL7R0Zm577Vof5IvkVZ48mx7fymrrNKMqV3q+LFnlLsW3XmJbVI875C5agVtlqTsSmMxg9GnEEQKbq7HMIrLCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a37f487cfd63d14ab8d8ec3eae5c4b595def1f44dfcfb5cb308c50562fd0ee0a","last_reissued_at":"2026-05-17T23:48:03.312497Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:03.312497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.09792","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":"2026-05-17T23:48:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SE1mYB/txI/h9f4ewOPWjAj0GAaeazhUVOIDYrLnG3CBfOaYUmlY1RKenPh0TWhenJ6IZgC0xF2wxeQDtr9wAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:41:15.135960Z"},"content_sha256":"88bb26c7bc9e7d0486c917029f5db312aad00bd0ccd509211940c61bfd6841fc","schema_version":"1.0","event_id":"sha256:88bb26c7bc9e7d0486c917029f5db312aad00bd0ccd509211940c61bfd6841fc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:UN7UQ7H5MPIUVOGY5Q7K4XCLLF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Unified Framework for Structured Graph Learning via Spectral Constraints","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG","cs.SI","math.OC"],"primary_cat":"stat.ML","authors_text":"Daniel Palomar, Jiaxi Ying, Jos\\'e Vin\\'icius de M. Cardoso, Sandeep Kumar","submitted_at":"2019-04-22T10:19:58Z","abstract_excerpt":"Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying graphical models from data. Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. Useful structured graphs include the multi-component graph, bipartite graph, connected graph, sparse graph, and regular graph. In general, structured graph learning is an NP-hard combinatorial problem, therefore"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.09792","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":"2026-05-17T23:48:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Cxuh7wGOrbqeqmPi688tSXM/NWvgFVdnlB7FIjLTu+/sr36Ee/q1FzFc+31Xljqfa+Ej+UgbNpYO3ZSIUdqAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:41:15.136727Z"},"content_sha256":"fd4552e3946a26b42028089ed393a0f20139849af7f400dea4af23b2d8174b90","schema_version":"1.0","event_id":"sha256:fd4552e3946a26b42028089ed393a0f20139849af7f400dea4af23b2d8174b90"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/bundle.json","state_url":"https://pith.science/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/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":"2026-06-11T21:41:15Z","links":{"resolver":"https://pith.science/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF","bundle":"https://pith.science/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/bundle.json","state":"https://pith.science/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UN7UQ7H5MPIUVOGY5Q7K4XCLLF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:UN7UQ7H5MPIUVOGY5Q7K4XCLLF","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":"24da5ffab58d60f42481ce32de9b77ae8dfb981d22db1e694e35d7a9c8464162","cross_cats_sorted":["cs.LG","cs.SI","math.OC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2019-04-22T10:19:58Z","title_canon_sha256":"456ebb04df67d8b3484ebf5b5bad33ec641261494b404190c354eb79aa5d41bc"},"schema_version":"1.0","source":{"id":"1904.09792","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.09792","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"arxiv_version","alias_value":"1904.09792v1","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.09792","created_at":"2026-05-17T23:48:03Z"},{"alias_kind":"pith_short_12","alias_value":"UN7UQ7H5MPIU","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_16","alias_value":"UN7UQ7H5MPIUVOGY","created_at":"2026-05-18T12:33:30Z"},{"alias_kind":"pith_short_8","alias_value":"UN7UQ7H5","created_at":"2026-05-18T12:33:30Z"}],"graph_snapshots":[{"event_id":"sha256:fd4552e3946a26b42028089ed393a0f20139849af7f400dea4af23b2d8174b90","target":"graph","created_at":"2026-05-17T23:48:03Z","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":"Graph learning from data represents a canonical problem that has received substantial attention in the literature. However, insufficient work has been done in incorporating prior structural knowledge onto the learning of underlying graphical models from data. Learning a graph with a specific structure is essential for interpretability and identification of the relationships among data. Useful structured graphs include the multi-component graph, bipartite graph, connected graph, sparse graph, and regular graph. In general, structured graph learning is an NP-hard combinatorial problem, therefore","authors_text":"Daniel Palomar, Jiaxi Ying, Jos\\'e Vin\\'icius de M. Cardoso, Sandeep Kumar","cross_cats":["cs.LG","cs.SI","math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2019-04-22T10:19:58Z","title":"A Unified Framework for Structured Graph Learning via Spectral Constraints"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.09792","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":"sha256:88bb26c7bc9e7d0486c917029f5db312aad00bd0ccd509211940c61bfd6841fc","target":"record","created_at":"2026-05-17T23:48:03Z","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":"24da5ffab58d60f42481ce32de9b77ae8dfb981d22db1e694e35d7a9c8464162","cross_cats_sorted":["cs.LG","cs.SI","math.OC"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2019-04-22T10:19:58Z","title_canon_sha256":"456ebb04df67d8b3484ebf5b5bad33ec641261494b404190c354eb79aa5d41bc"},"schema_version":"1.0","source":{"id":"1904.09792","kind":"arxiv","version":1}},"canonical_sha256":"a37f487cfd63d14ab8d8ec3eae5c4b595def1f44dfcfb5cb308c50562fd0ee0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a37f487cfd63d14ab8d8ec3eae5c4b595def1f44dfcfb5cb308c50562fd0ee0a","first_computed_at":"2026-05-17T23:48:03.312497Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:03.312497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bL7R0Zm577Vof5IvkVZ48mx7fymrrNKMqV3q+LFnlLsW3XmJbVI875C5agVtlqTsSmMxg9GnEEQKbq7HMIrLCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:03.313118Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.09792","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88bb26c7bc9e7d0486c917029f5db312aad00bd0ccd509211940c61bfd6841fc","sha256:fd4552e3946a26b42028089ed393a0f20139849af7f400dea4af23b2d8174b90"],"state_sha256":"31118543ddde956c2f4fc3b6ab12e9f2b5fbeb592fd9d1513d4bc1d4a8ae09cb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mr9r+XtpAvXv9bLbPi0vQFoNFSwBXhWpElCKLB68DWHClAmmqPx/2r92WXnq3+cnotj8KyAdcwVi4PclZ9VVDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T21:41:15.141193Z","bundle_sha256":"5c0bff1a2396f1b890a41759c1f272e56a7eba15a7eabf660641758b7d4bcc0c"}}