{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:SWQOD3HOF6SCYNOYCEYEYALZTX","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":"d421769cc9ccea79b8b2f592ebd9e9a042c7e3f93200184b6d44c3ed8fb6fbb7","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-21T17:03:21Z","title_canon_sha256":"2f539123a36e43fdbb689a5cd62fc2f07a9c543230247426c636457972da8310"},"schema_version":"1.0","source":{"id":"2311.12727","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.12727","created_at":"2026-07-05T07:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"2311.12727v2","created_at":"2026-07-05T07:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.12727","created_at":"2026-07-05T07:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"SWQOD3HOF6SC","created_at":"2026-07-05T07:16:04Z"},{"alias_kind":"pith_short_16","alias_value":"SWQOD3HOF6SCYNOY","created_at":"2026-07-05T07:16:04Z"},{"alias_kind":"pith_short_8","alias_value":"SWQOD3HO","created_at":"2026-07-05T07:16:04Z"}],"graph_snapshots":[{"event_id":"sha256:7b4dfba63647e0ae30bbce4b36ffaa635104f5e44b1897a47f8fa98e7d78d810","target":"graph","created_at":"2026-07-05T07:16:04Z","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/2311.12727/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Soft random sampling (SRS) is a simple yet effective approach for efficient training of large-scale deep neural networks when dealing with massive data. SRS selects a subset uniformly at random with replacement from the full data set in each epoch. In this paper, we conduct a theoretical and empirical analysis of SRS. First, we analyze its sampling dynamics including data coverage and occupancy. Next, we investigate its convergence with non-convex objective functions and give the convergence rate. Finally, we provide its generalization performance. We empirically evaluate SRS for image recogni","authors_text":"Ashish Mittal, Brian Kingsbury, George Saon, Songtao Lu, Wei Zhang, Xiaodong Cui","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-21T17:03:21Z","title":"Soft Random Sampling: A Theoretical and Empirical Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.12727","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:ffb6a3562475591154462e87fe449e62b5a6c2df0e4b18a026692e33de5d23b0","target":"record","created_at":"2026-07-05T07:16:04Z","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":"d421769cc9ccea79b8b2f592ebd9e9a042c7e3f93200184b6d44c3ed8fb6fbb7","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-11-21T17:03:21Z","title_canon_sha256":"2f539123a36e43fdbb689a5cd62fc2f07a9c543230247426c636457972da8310"},"schema_version":"1.0","source":{"id":"2311.12727","kind":"arxiv","version":2}},"canonical_sha256":"95a0e1ecee2fa42c35d811304c01799df141d2c7282316ed9a30facaa6bb6588","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95a0e1ecee2fa42c35d811304c01799df141d2c7282316ed9a30facaa6bb6588","first_computed_at":"2026-07-05T07:16:04.740191Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:16:04.740191Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"V55U5LBqEBkVJPzZkHL4lGtHG3VWeuksFRoRWF7AiheXq5A5wq8wGmU/FFFFeM70ZLyjBr5VG1spxc4grH8HAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:16:04.740686Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.12727","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ffb6a3562475591154462e87fe449e62b5a6c2df0e4b18a026692e33de5d23b0","sha256:7b4dfba63647e0ae30bbce4b36ffaa635104f5e44b1897a47f8fa98e7d78d810"],"state_sha256":"1cf10675271c37e01d851617720e9f9910effba250bbdd576ccedb9b75fefb37"}