{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:CREGFAKX5QAA7MRXHSQEG6KL6S","short_pith_number":"pith:CREGFAKX","canonical_record":{"source":{"id":"1904.05856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-04-11T17:23:41Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"b2f4a1b3c152e73493d591ae0385d5c974ef7aeeaead19ebf16fc14edf4394b7","abstract_canon_sha256":"334f3e36cc52ce250c7db90cf1febe8708b39e565d52cfbbc76a0c62eae91b88"},"schema_version":"1.0"},"canonical_sha256":"1448628157ec000fb2373ca043794bf483dacb485292761bbf11c4a0e8cf49ae","source":{"kind":"arxiv","id":"1904.05856","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05856","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05856v1","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05856","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_12","alias_value":"CREGFAKX5QAA","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_16","alias_value":"CREGFAKX5QAA7MRX","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_8","alias_value":"CREGFAKX","created_at":"2026-06-04T20:14:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:CREGFAKX5QAA7MRXHSQEG6KL6S","target":"record","payload":{"canonical_record":{"source":{"id":"1904.05856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-04-11T17:23:41Z","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"title_canon_sha256":"b2f4a1b3c152e73493d591ae0385d5c974ef7aeeaead19ebf16fc14edf4394b7","abstract_canon_sha256":"334f3e36cc52ce250c7db90cf1febe8708b39e565d52cfbbc76a0c62eae91b88"},"schema_version":"1.0"},"canonical_sha256":"1448628157ec000fb2373ca043794bf483dacb485292761bbf11c4a0e8cf49ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T20:14:24.630116Z","signature_b64":"q+BMxWAkn/SN7sR0tVl36VIagw/pmZrY10Ce2fOJeHT+olUAKUxPY48E3V2eUEpAKqEcGWtruH4Qeb16YwgwBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1448628157ec000fb2373ca043794bf483dacb485292761bbf11c4a0e8cf49ae","last_reissued_at":"2026-06-04T20:14:24.629634Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T20:14:24.629634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.05856","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":"2026-06-04T20:14:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JJNuDqWv2gIoau72Gvs2AMHqxX8W6k5My3JQH3BRwl5RdgQ3oeDCWfVyv5nHazRUt3496MTQBOt92ZKxejggDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T04:15:08.276439Z"},"content_sha256":"50fe9edf32f9051293906c6f47f042b002d2cdd688960e869aa0e4bad3b4fd45","schema_version":"1.0","event_id":"sha256:50fe9edf32f9051293906c6f47f042b002d2cdd688960e869aa0e4bad3b4fd45"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:CREGFAKX5QAA7MRXHSQEG6KL6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Connections Between Adaptive Control and Optimization in Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Anuradha M. Annaswamy, Eugene Lavretsky, Joseph E. Gaudio, Michael A. Bolender, Travis E. Gibson","submitted_at":"2019-04-11T17:23:41Z","abstract_excerpt":"This paper demonstrates many immediate connections between adaptive control and optimization methods commonly employed in machine learning. Starting from common output error formulations, similarities in update law modifications are examined. Concepts in stability, performance, and learning, common to both fields are then discussed. Building on the similarities in update laws and common concepts, new intersections and opportunities for improved algorithm analysis are provided. In particular, a specific problem related to higher order learning is solved through insights obtained from these inte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05856","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1904.05856/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-06-04T20:14:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M0k0JM49d9Eja6uJafPg400nxvcUlVKttEQIb06ca1owCh9JKx54phOXw5Fa4pDhYOdrTdLbW+F6CXFYw5sMCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T04:15:08.276836Z"},"content_sha256":"1967bb0eed061cfc465d3438a7f15485f0f89ff6603629e4536890e6c1f9321d","schema_version":"1.0","event_id":"sha256:1967bb0eed061cfc465d3438a7f15485f0f89ff6603629e4536890e6c1f9321d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/bundle.json","state_url":"https://pith.science/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/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":"2026-06-24T04:15:08Z","links":{"resolver":"https://pith.science/pith/CREGFAKX5QAA7MRXHSQEG6KL6S","bundle":"https://pith.science/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/bundle.json","state":"https://pith.science/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CREGFAKX5QAA7MRXHSQEG6KL6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:CREGFAKX5QAA7MRXHSQEG6KL6S","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":"334f3e36cc52ce250c7db90cf1febe8708b39e565d52cfbbc76a0c62eae91b88","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-04-11T17:23:41Z","title_canon_sha256":"b2f4a1b3c152e73493d591ae0385d5c974ef7aeeaead19ebf16fc14edf4394b7"},"schema_version":"1.0","source":{"id":"1904.05856","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05856","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05856v1","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05856","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_12","alias_value":"CREGFAKX5QAA","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_16","alias_value":"CREGFAKX5QAA7MRX","created_at":"2026-06-04T20:14:24Z"},{"alias_kind":"pith_short_8","alias_value":"CREGFAKX","created_at":"2026-06-04T20:14:24Z"}],"graph_snapshots":[{"event_id":"sha256:1967bb0eed061cfc465d3438a7f15485f0f89ff6603629e4536890e6c1f9321d","target":"graph","created_at":"2026-06-04T20:14:24Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1904.05856/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper demonstrates many immediate connections between adaptive control and optimization methods commonly employed in machine learning. Starting from common output error formulations, similarities in update law modifications are examined. Concepts in stability, performance, and learning, common to both fields are then discussed. Building on the similarities in update laws and common concepts, new intersections and opportunities for improved algorithm analysis are provided. In particular, a specific problem related to higher order learning is solved through insights obtained from these inte","authors_text":"Anuradha M. Annaswamy, Eugene Lavretsky, Joseph E. Gaudio, Michael A. Bolender, Travis E. Gibson","cross_cats":["cs.LG","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-04-11T17:23:41Z","title":"Connections Between Adaptive Control and Optimization in Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05856","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":"sha256:50fe9edf32f9051293906c6f47f042b002d2cdd688960e869aa0e4bad3b4fd45","target":"record","created_at":"2026-06-04T20:14:24Z","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":"334f3e36cc52ce250c7db90cf1febe8708b39e565d52cfbbc76a0c62eae91b88","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-04-11T17:23:41Z","title_canon_sha256":"b2f4a1b3c152e73493d591ae0385d5c974ef7aeeaead19ebf16fc14edf4394b7"},"schema_version":"1.0","source":{"id":"1904.05856","kind":"arxiv","version":1}},"canonical_sha256":"1448628157ec000fb2373ca043794bf483dacb485292761bbf11c4a0e8cf49ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1448628157ec000fb2373ca043794bf483dacb485292761bbf11c4a0e8cf49ae","first_computed_at":"2026-06-04T20:14:24.629634Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T20:14:24.629634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q+BMxWAkn/SN7sR0tVl36VIagw/pmZrY10Ce2fOJeHT+olUAKUxPY48E3V2eUEpAKqEcGWtruH4Qeb16YwgwBw==","signature_status":"signed_v1","signed_at":"2026-06-04T20:14:24.630116Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.05856","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50fe9edf32f9051293906c6f47f042b002d2cdd688960e869aa0e4bad3b4fd45","sha256:1967bb0eed061cfc465d3438a7f15485f0f89ff6603629e4536890e6c1f9321d"],"state_sha256":"180b2693d0112304b48704ee21dbdba35911e193cedbfa98d454da4928dab8fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZcZfLnti8P6oPrfGoj36/L5QLKxWH22Ieb+xAeS96WY3ofe5+UIjAu+Ik8t0PGZQxan8HQ59uenibVH5nfVvCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T04:15:08.278935Z","bundle_sha256":"484c7c7ec9133f930e3e672abdc87626c3bd589e972061030a8e2be0e9a1d9d6"}}