{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:O6QLXAO7NBPAWJLJJPC7VYWYSK","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":"a916656f5ce097fb78f48a436907b60de10f04ddd4dd130cd65b995e38ae303f","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-10-18T01:45:03Z","title_canon_sha256":"d7471110f9b91c72c8d2036fae278846a26cc70b844399bc85cbf7b4ce6764ae"},"schema_version":"1.0","source":{"id":"1910.08222","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.08222","created_at":"2026-07-05T06:54:52Z"},{"alias_kind":"arxiv_version","alias_value":"1910.08222v4","created_at":"2026-07-05T06:54:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.08222","created_at":"2026-07-05T06:54:52Z"},{"alias_kind":"pith_short_12","alias_value":"O6QLXAO7NBPA","created_at":"2026-07-05T06:54:52Z"},{"alias_kind":"pith_short_16","alias_value":"O6QLXAO7NBPAWJLJ","created_at":"2026-07-05T06:54:52Z"},{"alias_kind":"pith_short_8","alias_value":"O6QLXAO7","created_at":"2026-07-05T06:54:52Z"}],"graph_snapshots":[{"event_id":"sha256:58e00c483f3db53f0c3eb0b8ff721c762d13319749fe64c2c7debce36ad33a40","target":"graph","created_at":"2026-07-05T06:54:52Z","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/1910.08222/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mini-batch stochastic gradient descent (SGD) and variants thereof approximate the objective function's gradient with a small number of training examples, aka the batch size. Small batch sizes require little computation for each model update but can yield high-variance gradient estimates, which poses some challenges for optimization. Conversely, large batches require more computation but can yield higher precision gradient estimates. This work presents a method to adapt the batch size to the model's training loss. For various function classes, we show that our method requires the same order of ","authors_text":"Scott Sievert, Shrey Shah","cross_cats":["math.OC","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-10-18T01:45:03Z","title":"Improving the convergence of SGD through adaptive batch sizes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.08222","kind":"arxiv","version":4},"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":"sha256:5950298975cf807ac05c5a72695e94e9103595f915e630169954946a906517a3","target":"record","created_at":"2026-07-05T06:54:52Z","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":"a916656f5ce097fb78f48a436907b60de10f04ddd4dd130cd65b995e38ae303f","cross_cats_sorted":["math.OC","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-10-18T01:45:03Z","title_canon_sha256":"d7471110f9b91c72c8d2036fae278846a26cc70b844399bc85cbf7b4ce6764ae"},"schema_version":"1.0","source":{"id":"1910.08222","kind":"arxiv","version":4}},"canonical_sha256":"77a0bb81df685e0b25694bc5fae2d89290e3fd3010fd30f6cb73ea55d8d98737","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77a0bb81df685e0b25694bc5fae2d89290e3fd3010fd30f6cb73ea55d8d98737","first_computed_at":"2026-07-05T06:54:52.523473Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:54:52.523473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t8T5DDmyXCMlPlLK/lL3BKG4TkKCR+FjRoBh7CbEVgojZLI1BV1+Qqt//3WJAufT1kG9VtI7eMTKKWkkQcSCBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:54:52.523890Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.08222","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5950298975cf807ac05c5a72695e94e9103595f915e630169954946a906517a3","sha256:58e00c483f3db53f0c3eb0b8ff721c762d13319749fe64c2c7debce36ad33a40"],"state_sha256":"b89ddcbf33a4787770151a8c4bc096c78d3c0ed43d008cda2e54ba0b78738321"}