{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ULSK7XSOCSXFZNQA65BZY44RPT","short_pith_number":"pith:ULSK7XSO","canonical_record":{"source":{"id":"1910.02120","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-04T19:46:16Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b3486f72a5da1b922d7a5f8dac60dba61bec53359037ee7f9f4e3c591da912bd","abstract_canon_sha256":"acc9ff6bcc0feda16e174c2877ab02460011dff4d9cfb82552f5d6b0e9b95d11"},"schema_version":"1.0"},"canonical_sha256":"a2e4afde4e14ae5cb600f7439c73917cf303ee396828b64ac31bc099a947a862","source":{"kind":"arxiv","id":"1910.02120","version":7},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.02120","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"arxiv_version","alias_value":"1910.02120v7","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.02120","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_12","alias_value":"ULSK7XSOCSXF","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_16","alias_value":"ULSK7XSOCSXFZNQA","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_8","alias_value":"ULSK7XSO","created_at":"2026-07-05T04:15:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ULSK7XSOCSXFZNQA65BZY44RPT","target":"record","payload":{"canonical_record":{"source":{"id":"1910.02120","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-04T19:46:16Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b3486f72a5da1b922d7a5f8dac60dba61bec53359037ee7f9f4e3c591da912bd","abstract_canon_sha256":"acc9ff6bcc0feda16e174c2877ab02460011dff4d9cfb82552f5d6b0e9b95d11"},"schema_version":"1.0"},"canonical_sha256":"a2e4afde4e14ae5cb600f7439c73917cf303ee396828b64ac31bc099a947a862","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:15:26.510235Z","signature_b64":"VzDc6ufLItTShqgnKClI7GYok+PKZ5fXXi3OMmZDhSn4OOyYlFMlx8qi9ILlbCPEBIcLPxtF91+ZtJsa1lxKDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2e4afde4e14ae5cb600f7439c73917cf303ee396828b64ac31bc099a947a862","last_reissued_at":"2026-07-05T04:15:26.509794Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:15:26.509794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.02120","source_version":7,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:15:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d6d1/dqI/ZioaevdCL9w97Yqijm5g2OpD3ktIc5vAmg8GkRYjVQ3kaINyIQ+HehZnyGmwnRlDPQIMZReMLH5CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T05:32:16.127417Z"},"content_sha256":"a6b2019884b1667dcc9197272e63a84a4ac9a1266a3d26e7834441233f967d66","schema_version":"1.0","event_id":"sha256:a6b2019884b1667dcc9197272e63a84a4ac9a1266a3d26e7834441233f967d66"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ULSK7XSOCSXFZNQA65BZY44RPT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Distributed Learning of Deep Neural Networks using Independent Subnet Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Anastasios Kyrillidis, Binhang Yuan, Cameron R. Wolfe, Chen Dun, Christopher M. Jermaine, Yuxin Tang","submitted_at":"2019-10-04T19:46:16Z","abstract_excerpt":"Distributed machine learning (ML) can bring more computational resources to bear than single-machine learning, thus enabling reductions in training time. Distributed learning partitions models and data over many machines, allowing model and dataset sizes beyond the available compute power and memory of a single machine. In practice though, distributed ML is challenging when distribution is mandatory, rather than chosen by the practitioner. In such scenarios, data could unavoidably be separated among workers due to limited memory capacity per worker or even because of data privacy issues. There"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.02120","kind":"arxiv","version":7},"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/1910.02120/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":"2026-07-05T04:15:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QZRyk3+fNJUxS4xdxG38NyfEk9Se8eNkP4GGekETlK4D110fI7cm7y2ucI8uWpaOtwbnclyrX53zk/r1fWZqCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T05:32:16.128835Z"},"content_sha256":"bea76fe5d4419b0b37ee6dabf4f11707a1594854583fb359bc50fa43c915505b","schema_version":"1.0","event_id":"sha256:bea76fe5d4419b0b37ee6dabf4f11707a1594854583fb359bc50fa43c915505b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ULSK7XSOCSXFZNQA65BZY44RPT/bundle.json","state_url":"https://pith.science/pith/ULSK7XSOCSXFZNQA65BZY44RPT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ULSK7XSOCSXFZNQA65BZY44RPT/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":"2026-08-15T05:32:16Z","links":{"resolver":"https://pith.science/pith/ULSK7XSOCSXFZNQA65BZY44RPT","bundle":"https://pith.science/pith/ULSK7XSOCSXFZNQA65BZY44RPT/bundle.json","state":"https://pith.science/pith/ULSK7XSOCSXFZNQA65BZY44RPT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ULSK7XSOCSXFZNQA65BZY44RPT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ULSK7XSOCSXFZNQA65BZY44RPT","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":"acc9ff6bcc0feda16e174c2877ab02460011dff4d9cfb82552f5d6b0e9b95d11","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-04T19:46:16Z","title_canon_sha256":"b3486f72a5da1b922d7a5f8dac60dba61bec53359037ee7f9f4e3c591da912bd"},"schema_version":"1.0","source":{"id":"1910.02120","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.02120","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"arxiv_version","alias_value":"1910.02120v7","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.02120","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_12","alias_value":"ULSK7XSOCSXF","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_16","alias_value":"ULSK7XSOCSXFZNQA","created_at":"2026-07-05T04:15:26Z"},{"alias_kind":"pith_short_8","alias_value":"ULSK7XSO","created_at":"2026-07-05T04:15:26Z"}],"graph_snapshots":[{"event_id":"sha256:bea76fe5d4419b0b37ee6dabf4f11707a1594854583fb359bc50fa43c915505b","target":"graph","created_at":"2026-07-05T04:15:26Z","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/1910.02120/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed machine learning (ML) can bring more computational resources to bear than single-machine learning, thus enabling reductions in training time. Distributed learning partitions models and data over many machines, allowing model and dataset sizes beyond the available compute power and memory of a single machine. In practice though, distributed ML is challenging when distribution is mandatory, rather than chosen by the practitioner. In such scenarios, data could unavoidably be separated among workers due to limited memory capacity per worker or even because of data privacy issues. There","authors_text":"Anastasios Kyrillidis, Binhang Yuan, Cameron R. Wolfe, Chen Dun, Christopher M. Jermaine, Yuxin Tang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-04T19:46:16Z","title":"Distributed Learning of Deep Neural Networks using Independent Subnet Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.02120","kind":"arxiv","version":7},"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:a6b2019884b1667dcc9197272e63a84a4ac9a1266a3d26e7834441233f967d66","target":"record","created_at":"2026-07-05T04:15:26Z","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":"acc9ff6bcc0feda16e174c2877ab02460011dff4d9cfb82552f5d6b0e9b95d11","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-04T19:46:16Z","title_canon_sha256":"b3486f72a5da1b922d7a5f8dac60dba61bec53359037ee7f9f4e3c591da912bd"},"schema_version":"1.0","source":{"id":"1910.02120","kind":"arxiv","version":7}},"canonical_sha256":"a2e4afde4e14ae5cb600f7439c73917cf303ee396828b64ac31bc099a947a862","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a2e4afde4e14ae5cb600f7439c73917cf303ee396828b64ac31bc099a947a862","first_computed_at":"2026-07-05T04:15:26.509794Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:15:26.509794Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VzDc6ufLItTShqgnKClI7GYok+PKZ5fXXi3OMmZDhSn4OOyYlFMlx8qi9ILlbCPEBIcLPxtF91+ZtJsa1lxKDw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:15:26.510235Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.02120","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6b2019884b1667dcc9197272e63a84a4ac9a1266a3d26e7834441233f967d66","sha256:bea76fe5d4419b0b37ee6dabf4f11707a1594854583fb359bc50fa43c915505b"],"state_sha256":"cff49ed720898fbbb9431b26f96cbb0df5681121054c3c8e50c6fdc73f4b1d7c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7he83uXzg/9D/V53xGXM4Y2uFrx2twZSNtJ61zoaAtI3wxd5wFyxdVQOyVHugkVBlKUT6kDR0nRy57Wo44wOCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T05:32:16.136085Z","bundle_sha256":"fd69e78bd6901b1617d8bc7341cebf54b34b1c268b87ee6b86ae12fc198a0799"}}