{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4OA56NW3OYJGXLZAFIKCDZ3ZJI","short_pith_number":"pith:4OA56NW3","canonical_record":{"source":{"id":"1909.03631","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-09-09T04:27:57Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"905cab32aa382c7a1ce12ee2dc1c6ab595365eaf67c37df2b55aac318ac3927c","abstract_canon_sha256":"89b80c17166c9920d841c55698653df7d749949df2d00d58e9b3f301f0296b10"},"schema_version":"1.0"},"canonical_sha256":"e381df36db76126baf202a1421e7794a15108cf985b1fc071a5a3f0018bfc9b3","source":{"kind":"arxiv","id":"1909.03631","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.03631","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"arxiv_version","alias_value":"1909.03631v2","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.03631","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_12","alias_value":"4OA56NW3OYJG","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_16","alias_value":"4OA56NW3OYJGXLZA","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_8","alias_value":"4OA56NW3","created_at":"2026-07-05T00:29:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4OA56NW3OYJGXLZAFIKCDZ3ZJI","target":"record","payload":{"canonical_record":{"source":{"id":"1909.03631","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-09-09T04:27:57Z","cross_cats_sorted":["cs.LG","math.OC"],"title_canon_sha256":"905cab32aa382c7a1ce12ee2dc1c6ab595365eaf67c37df2b55aac318ac3927c","abstract_canon_sha256":"89b80c17166c9920d841c55698653df7d749949df2d00d58e9b3f301f0296b10"},"schema_version":"1.0"},"canonical_sha256":"e381df36db76126baf202a1421e7794a15108cf985b1fc071a5a3f0018bfc9b3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:29:28.938531Z","signature_b64":"OHjQ33L0k6P3gqEL77/+gevctsH/twZFz0R5zUGtXgHj/0E9AZmp23BZzxjWNveIl4Ysm/fZ3hlZT/6nIXStAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e381df36db76126baf202a1421e7794a15108cf985b1fc071a5a3f0018bfc9b3","last_reissued_at":"2026-07-05T00:29:28.938078Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:29:28.938078Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1909.03631","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":"2026-07-05T00:29:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bSJ+yZvaDOKDChybaknZR/kFN4RggnoXBjpd4iykMVtFxnOMYwAGuEN0u+TQN+OqBepqeQgXvNQmk1loZ461Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T01:27:10.897690Z"},"content_sha256":"4e9fff54ae58a5e138eefceb4989e36cc530b5ae1cf59eb9dedb8d8b449ad8b4","schema_version":"1.0","event_id":"sha256:4e9fff54ae58a5e138eefceb4989e36cc530b5ae1cf59eb9dedb8d8b449ad8b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4OA56NW3OYJGXLZAFIKCDZ3ZJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Communication-Censored Distributed Stochastic Gradient Descent","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.OC"],"primary_cat":"stat.ML","authors_text":"Liping Li, Qing Ling, Tianyi Chen, Weiyu Li, Zhaoxian Wu","submitted_at":"2019-09-09T04:27:57Z","abstract_excerpt":"This paper develops a communication-efficient algorithm to solve the stochastic optimization problem defined over a distributed network, aiming at reducing the burdensome communication in applications such as distributed machine learning.Different from the existing works based on quantization and sparsification, we introduce a communication-censoring technique to reduce the transmissions of variables, which leads to our communication-Censored distributed Stochastic Gradient Descent (CSGD) algorithm. Specifically, in CSGD, the latest mini-batch stochastic gradient at a worker will be transmitte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.03631","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/1909.03631/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":"2026-07-05T00:29:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vz+7DKNIolbCnMc1HXfUT/UpuLFpYq/1gw01MPKBkyoyqUJS5h6lOuN2jo3ZIcrdPG1sE0pF56/l0mT/6Lv/BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T01:27:10.898313Z"},"content_sha256":"5a45217a91e777cfe0f435183bfb18b9a1e63611561371b280115a6961a88a3f","schema_version":"1.0","event_id":"sha256:5a45217a91e777cfe0f435183bfb18b9a1e63611561371b280115a6961a88a3f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/bundle.json","state_url":"https://pith.science/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/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":"2026-08-14T01:27:10Z","links":{"resolver":"https://pith.science/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI","bundle":"https://pith.science/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/bundle.json","state":"https://pith.science/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4OA56NW3OYJGXLZAFIKCDZ3ZJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4OA56NW3OYJGXLZAFIKCDZ3ZJI","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":"89b80c17166c9920d841c55698653df7d749949df2d00d58e9b3f301f0296b10","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-09-09T04:27:57Z","title_canon_sha256":"905cab32aa382c7a1ce12ee2dc1c6ab595365eaf67c37df2b55aac318ac3927c"},"schema_version":"1.0","source":{"id":"1909.03631","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.03631","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"arxiv_version","alias_value":"1909.03631v2","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.03631","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_12","alias_value":"4OA56NW3OYJG","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_16","alias_value":"4OA56NW3OYJGXLZA","created_at":"2026-07-05T00:29:28Z"},{"alias_kind":"pith_short_8","alias_value":"4OA56NW3","created_at":"2026-07-05T00:29:28Z"}],"graph_snapshots":[{"event_id":"sha256:5a45217a91e777cfe0f435183bfb18b9a1e63611561371b280115a6961a88a3f","target":"graph","created_at":"2026-07-05T00:29:28Z","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/1909.03631/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper develops a communication-efficient algorithm to solve the stochastic optimization problem defined over a distributed network, aiming at reducing the burdensome communication in applications such as distributed machine learning.Different from the existing works based on quantization and sparsification, we introduce a communication-censoring technique to reduce the transmissions of variables, which leads to our communication-Censored distributed Stochastic Gradient Descent (CSGD) algorithm. Specifically, in CSGD, the latest mini-batch stochastic gradient at a worker will be transmitte","authors_text":"Liping Li, Qing Ling, Tianyi Chen, Weiyu Li, Zhaoxian Wu","cross_cats":["cs.LG","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-09-09T04:27:57Z","title":"Communication-Censored Distributed Stochastic Gradient Descent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.03631","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":"sha256:4e9fff54ae58a5e138eefceb4989e36cc530b5ae1cf59eb9dedb8d8b449ad8b4","target":"record","created_at":"2026-07-05T00:29:28Z","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":"89b80c17166c9920d841c55698653df7d749949df2d00d58e9b3f301f0296b10","cross_cats_sorted":["cs.LG","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-09-09T04:27:57Z","title_canon_sha256":"905cab32aa382c7a1ce12ee2dc1c6ab595365eaf67c37df2b55aac318ac3927c"},"schema_version":"1.0","source":{"id":"1909.03631","kind":"arxiv","version":2}},"canonical_sha256":"e381df36db76126baf202a1421e7794a15108cf985b1fc071a5a3f0018bfc9b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e381df36db76126baf202a1421e7794a15108cf985b1fc071a5a3f0018bfc9b3","first_computed_at":"2026-07-05T00:29:28.938078Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:29:28.938078Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OHjQ33L0k6P3gqEL77/+gevctsH/twZFz0R5zUGtXgHj/0E9AZmp23BZzxjWNveIl4Ysm/fZ3hlZT/6nIXStAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:29:28.938531Z","signed_message":"canonical_sha256_bytes"},"source_id":"1909.03631","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e9fff54ae58a5e138eefceb4989e36cc530b5ae1cf59eb9dedb8d8b449ad8b4","sha256:5a45217a91e777cfe0f435183bfb18b9a1e63611561371b280115a6961a88a3f"],"state_sha256":"3af4ac4b9166684ade55179c3850de0cfd62bd80f01f221ccdfed03ffc381d6c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yzwtIGMUkXdj/b2Krw+y5Es/sF1lk+Pw2lUyE/Do/GfsihCwDT6/5PrA0a8z/76DFo8fb+5SXw6VJlNIe9f9Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T01:27:10.905041Z","bundle_sha256":"ad5f374e717b52b2387226c4bcd99d5b62add19e1122e7b3f942cf683ad8d347"}}