{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:AF6RZYSZNXTHSO2DC3PXPHFCJN","short_pith_number":"pith:AF6RZYSZ","canonical_record":{"source":{"id":"2011.01718","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-11-03T14:11:52Z","cross_cats_sorted":[],"title_canon_sha256":"0978ca0b705a2da5e363933fde5ce2948a471087e3c2817d60f1a0e8f776a3ed","abstract_canon_sha256":"e0ac1695c18566e054fa1f71b80a42c3a1e2fb04264afd336794dc0cf288cab8"},"schema_version":"1.0"},"canonical_sha256":"017d1ce2596de6793b4316df779ca24b5eedb2034af4d9ba791d469075453623","source":{"kind":"arxiv","id":"2011.01718","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.01718","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"arxiv_version","alias_value":"2011.01718v5","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.01718","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_12","alias_value":"AF6RZYSZNXTH","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_16","alias_value":"AF6RZYSZNXTHSO2D","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_8","alias_value":"AF6RZYSZ","created_at":"2026-05-20T00:05:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:AF6RZYSZNXTHSO2DC3PXPHFCJN","target":"record","payload":{"canonical_record":{"source":{"id":"2011.01718","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-11-03T14:11:52Z","cross_cats_sorted":[],"title_canon_sha256":"0978ca0b705a2da5e363933fde5ce2948a471087e3c2817d60f1a0e8f776a3ed","abstract_canon_sha256":"e0ac1695c18566e054fa1f71b80a42c3a1e2fb04264afd336794dc0cf288cab8"},"schema_version":"1.0"},"canonical_sha256":"017d1ce2596de6793b4316df779ca24b5eedb2034af4d9ba791d469075453623","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:23.616625Z","signature_b64":"QMPkP169ah8nroiK96V5mRD/2kZ+EtQdNfudNP8ScGPMV2RseS+fS9V5eikhKJntUPWwEg9njq5BrmBPu+kkAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"017d1ce2596de6793b4316df779ca24b5eedb2034af4d9ba791d469075453623","last_reissued_at":"2026-05-20T00:05:23.615984Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:23.615984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.01718","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":"2026-05-20T00:05:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3s/eeP6HR90NP0fr+wiHwAR5CqTHRyoZkdvl53pzz6Fp8OjKK0os7acanK3kZKV14Shg4Mon0y2Qh0SBsv+JAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T16:39:48.768299Z"},"content_sha256":"652c7096689c51dd3602e4be78e15de55b3042d9e2065ec40707400546c294f2","schema_version":"1.0","event_id":"sha256:652c7096689c51dd3602e4be78e15de55b3042d9e2065ec40707400546c294f2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:AF6RZYSZNXTHSO2DC3PXPHFCJN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Iteration Stochastic Optimizers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Andre Carlon, Luis Espath, Rafael Lopez, Raul Tempone","submitted_at":"2020-11-03T14:11:52Z","abstract_excerpt":"We introduce Multi-Iteration Stochastic Optimizers, a novel class of first-order stochastic methods that control the relative $L^2$ error using successive control variates along the iteration path. By exploiting correlations between iterates, these control variates reduce the estimator's variance, making an accurate mean gradient estimation computationally affordable. Our approach centers on the Multi-Iteration stochastiC Estimator (MICE), which can be seamlessly coupled with any first-order stochastic optimizer due to its non-intrusive design. The algorithm adaptively selects which iterates t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.01718","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2011.01718/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":"2026-05-20T00:05:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OH1d09LyG2PaSXEcqk+cbKjdOTrrXsu9IN+eDStcVnNvD3L8mjAZn9/wR7u6c6vAozTWZ9H4+hRN3wmBgYQRCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T16:39:48.768693Z"},"content_sha256":"04cb1c744eaf31187298d8a5a1217ba53be162648040deec92f3bb79c4e64c65","schema_version":"1.0","event_id":"sha256:04cb1c744eaf31187298d8a5a1217ba53be162648040deec92f3bb79c4e64c65"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/bundle.json","state_url":"https://pith.science/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/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":"2026-06-05T16:39:48Z","links":{"resolver":"https://pith.science/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN","bundle":"https://pith.science/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/bundle.json","state":"https://pith.science/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AF6RZYSZNXTHSO2DC3PXPHFCJN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:AF6RZYSZNXTHSO2DC3PXPHFCJN","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":"e0ac1695c18566e054fa1f71b80a42c3a1e2fb04264afd336794dc0cf288cab8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-11-03T14:11:52Z","title_canon_sha256":"0978ca0b705a2da5e363933fde5ce2948a471087e3c2817d60f1a0e8f776a3ed"},"schema_version":"1.0","source":{"id":"2011.01718","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.01718","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"arxiv_version","alias_value":"2011.01718v5","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.01718","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_12","alias_value":"AF6RZYSZNXTH","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_16","alias_value":"AF6RZYSZNXTHSO2D","created_at":"2026-05-20T00:05:23Z"},{"alias_kind":"pith_short_8","alias_value":"AF6RZYSZ","created_at":"2026-05-20T00:05:23Z"}],"graph_snapshots":[{"event_id":"sha256:04cb1c744eaf31187298d8a5a1217ba53be162648040deec92f3bb79c4e64c65","target":"graph","created_at":"2026-05-20T00:05:23Z","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/2011.01718/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce Multi-Iteration Stochastic Optimizers, a novel class of first-order stochastic methods that control the relative $L^2$ error using successive control variates along the iteration path. By exploiting correlations between iterates, these control variates reduce the estimator's variance, making an accurate mean gradient estimation computationally affordable. Our approach centers on the Multi-Iteration stochastiC Estimator (MICE), which can be seamlessly coupled with any first-order stochastic optimizer due to its non-intrusive design. The algorithm adaptively selects which iterates t","authors_text":"Andre Carlon, Luis Espath, Rafael Lopez, Raul Tempone","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-11-03T14:11:52Z","title":"Multi-Iteration Stochastic Optimizers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.01718","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":"sha256:652c7096689c51dd3602e4be78e15de55b3042d9e2065ec40707400546c294f2","target":"record","created_at":"2026-05-20T00:05:23Z","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":"e0ac1695c18566e054fa1f71b80a42c3a1e2fb04264afd336794dc0cf288cab8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-11-03T14:11:52Z","title_canon_sha256":"0978ca0b705a2da5e363933fde5ce2948a471087e3c2817d60f1a0e8f776a3ed"},"schema_version":"1.0","source":{"id":"2011.01718","kind":"arxiv","version":5}},"canonical_sha256":"017d1ce2596de6793b4316df779ca24b5eedb2034af4d9ba791d469075453623","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"017d1ce2596de6793b4316df779ca24b5eedb2034af4d9ba791d469075453623","first_computed_at":"2026-05-20T00:05:23.615984Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:23.615984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QMPkP169ah8nroiK96V5mRD/2kZ+EtQdNfudNP8ScGPMV2RseS+fS9V5eikhKJntUPWwEg9njq5BrmBPu+kkAg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:23.616625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.01718","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:652c7096689c51dd3602e4be78e15de55b3042d9e2065ec40707400546c294f2","sha256:04cb1c744eaf31187298d8a5a1217ba53be162648040deec92f3bb79c4e64c65"],"state_sha256":"96013411193a002337f0f00674ce2a65cb192f0bffdf0c0f1e7554cde0606ea2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jTgaotpBW/rnxuEH+x15Vh4xe2ewqOpFYyvKzOddsgwhX5hHVxSPABfqzecVssFVYY64EIMBqQ56+GgS+4HOCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T16:39:48.770945Z","bundle_sha256":"3eacf731b3dd752290ab6e3e7da4603e0b11b256b64b400795377c0ec6042d14"}}