{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2CPOXPHVLJKIEVQ7IIZTPLXWAG","short_pith_number":"pith:2CPOXPHV","canonical_record":{"source":{"id":"2503.19155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2025-03-24T21:22:53Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"32a066ab5e117c80b50bcfdae6c0466ed5c707256cc9d88abd946e91fb455c19","abstract_canon_sha256":"1ef89a9ca1d6d266c878f1b893f9007ca7f710f7e003f88542ec3739709db8b5"},"schema_version":"1.0"},"canonical_sha256":"d09eebbcf55a5482561f423337aef601ac9a73c07daddca580c4132e03859cc9","source":{"kind":"arxiv","id":"2503.19155","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.19155","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"arxiv_version","alias_value":"2503.19155v1","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.19155","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_12","alias_value":"2CPOXPHVLJKI","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_16","alias_value":"2CPOXPHVLJKIEVQ7","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_8","alias_value":"2CPOXPHV","created_at":"2026-07-05T10:38:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2CPOXPHVLJKIEVQ7IIZTPLXWAG","target":"record","payload":{"canonical_record":{"source":{"id":"2503.19155","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2025-03-24T21:22:53Z","cross_cats_sorted":["cs.NA"],"title_canon_sha256":"32a066ab5e117c80b50bcfdae6c0466ed5c707256cc9d88abd946e91fb455c19","abstract_canon_sha256":"1ef89a9ca1d6d266c878f1b893f9007ca7f710f7e003f88542ec3739709db8b5"},"schema_version":"1.0"},"canonical_sha256":"d09eebbcf55a5482561f423337aef601ac9a73c07daddca580c4132e03859cc9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:38:50.669448Z","signature_b64":"KvljEd3A6GVNBHhK8Wrk1lPlgNpNytMpoawsghq4wAW5iQ03U8iRo9dl0VrEsM6wEZ80G+BT3j+TQRxtYkJKAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d09eebbcf55a5482561f423337aef601ac9a73c07daddca580c4132e03859cc9","last_reissued_at":"2026-07-05T10:38:50.668917Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:38:50.668917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.19155","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":"2026-07-05T10:38:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+SYTSWoS850pHdqcfSpTt0+z2NTsPSsuWqYDrzEXDEaVpRnBqP+HI0XfSSo8tXHwly3hYlwWmECI+BxkLmQGBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:26:14.806308Z"},"content_sha256":"b3213d276b1108ebebbc048efadf3d37f9e5aa5e77c8f16857f506bdd85c9cfd","schema_version":"1.0","event_id":"sha256:b3213d276b1108ebebbc048efadf3d37f9e5aa5e77c8f16857f506bdd85c9cfd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2CPOXPHVLJKIEVQ7IIZTPLXWAG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Block Gauss-Seidel methods for t-product tensor regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NA"],"primary_cat":"math.NA","authors_text":"Alejandra Castillo, Alona Kryshchenko, Deanna Needell, Iryna Hartsock, Jamie Haddock, Kamila Larripa, Karamatou Yacoubou Djima, Lara Kassab, Paulina Hoyos, Shambhavi Suryanarayanan","submitted_at":"2025-03-24T21:22:53Z","abstract_excerpt":"Randomized iterative algorithms, such as the randomized Kaczmarz method and the randomized Gauss-Seidel method, have gained considerable popularity due to their efficacy in solving matrix-vector and matrix-matrix regression problems. Our present work leverages the insights gained from studying such algorithms to develop regression methods for tensors, which are the natural setting for many application problems, e.g., image deblurring. In particular, we extend two variants of the block-randomized Gauss-Seidel method to solve a t-product tensor regression problem. We additionally develop methods"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.19155","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/2503.19155/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":"2026-07-05T10:38:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5oFPw/+Wy+Yt7tibSQYDtYHM8DSgr3niclB8dSQ4RXBAmXwdHHdD/xi0v9FNQepLWPNoxCDUrGEeg4L49GjnBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:26:14.806691Z"},"content_sha256":"2cdec21abca97ba2df3ca374ed019e078bef114d5c31fbe71647da9fbb476803","schema_version":"1.0","event_id":"sha256:2cdec21abca97ba2df3ca374ed019e078bef114d5c31fbe71647da9fbb476803"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/bundle.json","state_url":"https://pith.science/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/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":"2026-07-07T10:26:14Z","links":{"resolver":"https://pith.science/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG","bundle":"https://pith.science/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/bundle.json","state":"https://pith.science/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2CPOXPHVLJKIEVQ7IIZTPLXWAG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2CPOXPHVLJKIEVQ7IIZTPLXWAG","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":"1ef89a9ca1d6d266c878f1b893f9007ca7f710f7e003f88542ec3739709db8b5","cross_cats_sorted":["cs.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2025-03-24T21:22:53Z","title_canon_sha256":"32a066ab5e117c80b50bcfdae6c0466ed5c707256cc9d88abd946e91fb455c19"},"schema_version":"1.0","source":{"id":"2503.19155","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.19155","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"arxiv_version","alias_value":"2503.19155v1","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.19155","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_12","alias_value":"2CPOXPHVLJKI","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_16","alias_value":"2CPOXPHVLJKIEVQ7","created_at":"2026-07-05T10:38:50Z"},{"alias_kind":"pith_short_8","alias_value":"2CPOXPHV","created_at":"2026-07-05T10:38:50Z"}],"graph_snapshots":[{"event_id":"sha256:2cdec21abca97ba2df3ca374ed019e078bef114d5c31fbe71647da9fbb476803","target":"graph","created_at":"2026-07-05T10:38:50Z","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/2503.19155/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Randomized iterative algorithms, such as the randomized Kaczmarz method and the randomized Gauss-Seidel method, have gained considerable popularity due to their efficacy in solving matrix-vector and matrix-matrix regression problems. Our present work leverages the insights gained from studying such algorithms to develop regression methods for tensors, which are the natural setting for many application problems, e.g., image deblurring. In particular, we extend two variants of the block-randomized Gauss-Seidel method to solve a t-product tensor regression problem. We additionally develop methods","authors_text":"Alejandra Castillo, Alona Kryshchenko, Deanna Needell, Iryna Hartsock, Jamie Haddock, Kamila Larripa, Karamatou Yacoubou Djima, Lara Kassab, Paulina Hoyos, Shambhavi Suryanarayanan","cross_cats":["cs.NA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2025-03-24T21:22:53Z","title":"Block Gauss-Seidel methods for t-product tensor regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.19155","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:b3213d276b1108ebebbc048efadf3d37f9e5aa5e77c8f16857f506bdd85c9cfd","target":"record","created_at":"2026-07-05T10:38:50Z","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":"1ef89a9ca1d6d266c878f1b893f9007ca7f710f7e003f88542ec3739709db8b5","cross_cats_sorted":["cs.NA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2025-03-24T21:22:53Z","title_canon_sha256":"32a066ab5e117c80b50bcfdae6c0466ed5c707256cc9d88abd946e91fb455c19"},"schema_version":"1.0","source":{"id":"2503.19155","kind":"arxiv","version":1}},"canonical_sha256":"d09eebbcf55a5482561f423337aef601ac9a73c07daddca580c4132e03859cc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d09eebbcf55a5482561f423337aef601ac9a73c07daddca580c4132e03859cc9","first_computed_at":"2026-07-05T10:38:50.668917Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:38:50.668917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KvljEd3A6GVNBHhK8Wrk1lPlgNpNytMpoawsghq4wAW5iQ03U8iRo9dl0VrEsM6wEZ80G+BT3j+TQRxtYkJKAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:38:50.669448Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.19155","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3213d276b1108ebebbc048efadf3d37f9e5aa5e77c8f16857f506bdd85c9cfd","sha256:2cdec21abca97ba2df3ca374ed019e078bef114d5c31fbe71647da9fbb476803"],"state_sha256":"42aaebc3e84909478c78a75ad03ee13ab9321594549747f2534a2edb3b202056"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ciCWx3QfI/pQ6KXrfruVWxqPNrBzdgQOAVhvHWmf7y4VQzypPYJJmF4jCZAGaby76FWmcjvLLcqd6cz/sS6xCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T10:26:14.808672Z","bundle_sha256":"4b64b20a960605b98e5450dc5af65224ff78b757c70523ba7d994af67beeb59a"}}