{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:6UUDLCCFQVT7SYOQGLJ6LRXC3T","short_pith_number":"pith:6UUDLCCF","canonical_record":{"source":{"id":"2412.12180","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.OC","submitted_at":"2024-12-13T08:22:07Z","cross_cats_sorted":["cs.NA","math.NA"],"title_canon_sha256":"dc6f77d724dc4ded2d2adef00ac5e2ea2849a52e2e8ec8f8cbe8c3171f8dd00c","abstract_canon_sha256":"03db9a2c84e0f377c0d229060d0c5a8733e22cb5ea69e442d130ee19ecccf282"},"schema_version":"1.0"},"canonical_sha256":"f5283588458567f961d032d3e5c6e2dce1f34b0a0249d5ea2b9986278e9241b2","source":{"kind":"arxiv","id":"2412.12180","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12180","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12180v2","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12180","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_12","alias_value":"6UUDLCCFQVT7","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_16","alias_value":"6UUDLCCFQVT7SYOQ","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_8","alias_value":"6UUDLCCF","created_at":"2026-07-05T11:45:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:6UUDLCCFQVT7SYOQGLJ6LRXC3T","target":"record","payload":{"canonical_record":{"source":{"id":"2412.12180","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.OC","submitted_at":"2024-12-13T08:22:07Z","cross_cats_sorted":["cs.NA","math.NA"],"title_canon_sha256":"dc6f77d724dc4ded2d2adef00ac5e2ea2849a52e2e8ec8f8cbe8c3171f8dd00c","abstract_canon_sha256":"03db9a2c84e0f377c0d229060d0c5a8733e22cb5ea69e442d130ee19ecccf282"},"schema_version":"1.0"},"canonical_sha256":"f5283588458567f961d032d3e5c6e2dce1f34b0a0249d5ea2b9986278e9241b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:54.824612Z","signature_b64":"HmUqZWYPVNKxSR+h0GMfSWOSPRz1/Yv4w+8qAtYWw/AhJ+Svb8rVOL13HiMr+jl5Is827BPVo7AM88UuXjZRDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5283588458567f961d032d3e5c6e2dce1f34b0a0249d5ea2b9986278e9241b2","last_reissued_at":"2026-07-05T11:45:54.824047Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:54.824047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.12180","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:45:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EiM1LoVCqPU4jJA9ScpRzGABErBW6rmoId7yKkR47rUIuZKc7MmXz5m4q2fyqorT1yayKcJ1Zof4tnD4D0FuDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:01:01.118704Z"},"content_sha256":"e254f6b35dfbd2f81847363f7bb77b872a320c86cea4d47962bee8a5b42a3d4a","schema_version":"1.0","event_id":"sha256:e254f6b35dfbd2f81847363f7bb77b872a320c86cea4d47962bee8a5b42a3d4a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:6UUDLCCFQVT7SYOQGLJ6LRXC3T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fully stochastic trust-region methods with Barzilai-Borwein steplengths","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.NA","math.NA"],"primary_cat":"math.OC","authors_text":"Benedetta Morini, Mahsa Yousefi, Stefania Bellavia","submitted_at":"2024-12-13T08:22:07Z","abstract_excerpt":"We investigate stochastic gradient methods and stochastic counterparts of the Barzilai-Borwein steplengths and their application to finite-sum minimization problems. Our proposal is based on the Trust-Region-ish (TRish) framework introduced in [F. E. Curtis, K. Scheinberg, R. Shi, {\\it A stochastic trust region algorithm based on careful step normalization}, Informs Journal on Optimization, 1, 2019]. The new framework, named TRishBB, aims to enhance the performance of TRish and at reducing the computational cost of the second-order TRish variant. We propose three different methods belonging to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12180","kind":"arxiv","version":2},"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/2412.12180/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":"2026-07-05T11:45:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uPfoOtftHI5ZAJOX9eb6a1GH2pL7n2wypQfQ536pMBWFJmgnpmcfjTajpLhLIl1Qta/NJEvu7EBeIiLg1R4oAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T17:01:01.119647Z"},"content_sha256":"1b26df8d57d75105ceac9eaeaf99def2821db9d13d0d49e70f4c0a44cf5d1571","schema_version":"1.0","event_id":"sha256:1b26df8d57d75105ceac9eaeaf99def2821db9d13d0d49e70f4c0a44cf5d1571"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/bundle.json","state_url":"https://pith.science/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/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":"2026-08-19T17:01:01Z","links":{"resolver":"https://pith.science/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T","bundle":"https://pith.science/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/bundle.json","state":"https://pith.science/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6UUDLCCFQVT7SYOQGLJ6LRXC3T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6UUDLCCFQVT7SYOQGLJ6LRXC3T","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":"03db9a2c84e0f377c0d229060d0c5a8733e22cb5ea69e442d130ee19ecccf282","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.OC","submitted_at":"2024-12-13T08:22:07Z","title_canon_sha256":"dc6f77d724dc4ded2d2adef00ac5e2ea2849a52e2e8ec8f8cbe8c3171f8dd00c"},"schema_version":"1.0","source":{"id":"2412.12180","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.12180","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"arxiv_version","alias_value":"2412.12180v2","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.12180","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_12","alias_value":"6UUDLCCFQVT7","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_16","alias_value":"6UUDLCCFQVT7SYOQ","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_8","alias_value":"6UUDLCCF","created_at":"2026-07-05T11:45:54Z"}],"graph_snapshots":[{"event_id":"sha256:1b26df8d57d75105ceac9eaeaf99def2821db9d13d0d49e70f4c0a44cf5d1571","target":"graph","created_at":"2026-07-05T11:45:54Z","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/2412.12180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate stochastic gradient methods and stochastic counterparts of the Barzilai-Borwein steplengths and their application to finite-sum minimization problems. Our proposal is based on the Trust-Region-ish (TRish) framework introduced in [F. E. Curtis, K. Scheinberg, R. Shi, {\\it A stochastic trust region algorithm based on careful step normalization}, Informs Journal on Optimization, 1, 2019]. The new framework, named TRishBB, aims to enhance the performance of TRish and at reducing the computational cost of the second-order TRish variant. We propose three different methods belonging to","authors_text":"Benedetta Morini, Mahsa Yousefi, Stefania Bellavia","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.OC","submitted_at":"2024-12-13T08:22:07Z","title":"Fully stochastic trust-region methods with Barzilai-Borwein steplengths"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.12180","kind":"arxiv","version":2},"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:e254f6b35dfbd2f81847363f7bb77b872a320c86cea4d47962bee8a5b42a3d4a","target":"record","created_at":"2026-07-05T11:45:54Z","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":"03db9a2c84e0f377c0d229060d0c5a8733e22cb5ea69e442d130ee19ecccf282","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"math.OC","submitted_at":"2024-12-13T08:22:07Z","title_canon_sha256":"dc6f77d724dc4ded2d2adef00ac5e2ea2849a52e2e8ec8f8cbe8c3171f8dd00c"},"schema_version":"1.0","source":{"id":"2412.12180","kind":"arxiv","version":2}},"canonical_sha256":"f5283588458567f961d032d3e5c6e2dce1f34b0a0249d5ea2b9986278e9241b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f5283588458567f961d032d3e5c6e2dce1f34b0a0249d5ea2b9986278e9241b2","first_computed_at":"2026-07-05T11:45:54.824047Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:54.824047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HmUqZWYPVNKxSR+h0GMfSWOSPRz1/Yv4w+8qAtYWw/AhJ+Svb8rVOL13HiMr+jl5Is827BPVo7AM88UuXjZRDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:54.824612Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.12180","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e254f6b35dfbd2f81847363f7bb77b872a320c86cea4d47962bee8a5b42a3d4a","sha256:1b26df8d57d75105ceac9eaeaf99def2821db9d13d0d49e70f4c0a44cf5d1571"],"state_sha256":"d3f0dc02f30648e42eda02ae8e47436fbc4cdc53680f2865a3f50112c857abc8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i5zxdCuBvVbekVa4TArBImBcZNp/7QkOe5VbOCYwMFrNs90u9tgk8cXOgoivz3sk8zLm2VnbNLMFfu+IcHOVCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T17:01:01.125907Z","bundle_sha256":"83f4db8f8c929c5a853bc244b1e53d31cbda49d98441ec2d74e5a396b42ec180"}}