{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:BQ2GPDBX35F23QPHKDNHHY3AD6","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":"adc00f782b87cbc7735cbf86f6ad408817e1b471233f2546b1a6bbe5e7c1d524","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-11T21:39:53Z","title_canon_sha256":"0103b35c4237d3de870c4ccf80b2191a44c061176536431054dc6e828725b2c1"},"schema_version":"1.0","source":{"id":"2102.06280","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.06280","created_at":"2026-07-05T02:14:46Z"},{"alias_kind":"arxiv_version","alias_value":"2102.06280v1","created_at":"2026-07-05T02:14:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.06280","created_at":"2026-07-05T02:14:46Z"},{"alias_kind":"pith_short_12","alias_value":"BQ2GPDBX35F2","created_at":"2026-07-05T02:14:46Z"},{"alias_kind":"pith_short_16","alias_value":"BQ2GPDBX35F23QPH","created_at":"2026-07-05T02:14:46Z"},{"alias_kind":"pith_short_8","alias_value":"BQ2GPDBX","created_at":"2026-07-05T02:14:46Z"}],"graph_snapshots":[{"event_id":"sha256:918ed72ad6eb505566e7f8a86223352c289d395014f62d59cba127dd3f304a61","target":"graph","created_at":"2026-07-05T02:14:46Z","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/2102.06280/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the increasing demand for large-scale training of machine learning models, consensus-based distributed optimization methods have recently been advocated as alternatives to the popular parameter server framework. In this paradigm, each worker maintains a local estimate of the optimal parameter vector, and iteratively updates it by waiting and averaging all estimates obtained from its neighbors, and then corrects it on the basis of its local dataset. However, the synchronization phase can be time consuming due to the need to wait for \\textit{stragglers}, i.e., slower workers. An efficient w","authors_text":"Gang Yan, Guojun Xiong, Jian Li, Rahul Singh","cross_cats":["cs.DC","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-11T21:39:53Z","title":"Straggler-Resilient Distributed Machine Learning with Dynamic Backup Workers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.06280","kind":"arxiv","version":1},"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":"sha256:07295e37f54ec3e686a949cecaeb77cd4c166cd92fe7bbb9c6fecbe9bb9c6377","target":"record","created_at":"2026-07-05T02:14:46Z","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":"adc00f782b87cbc7735cbf86f6ad408817e1b471233f2546b1a6bbe5e7c1d524","cross_cats_sorted":["cs.DC","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-02-11T21:39:53Z","title_canon_sha256":"0103b35c4237d3de870c4ccf80b2191a44c061176536431054dc6e828725b2c1"},"schema_version":"1.0","source":{"id":"2102.06280","kind":"arxiv","version":1}},"canonical_sha256":"0c34678c37df4badc1e750da73e3601fb585ad2a897bfbde3623bf68821af858","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c34678c37df4badc1e750da73e3601fb585ad2a897bfbde3623bf68821af858","first_computed_at":"2026-07-05T02:14:46.485343Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:14:46.485343Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5740ovpRceOuq2Wsde3D4bejBtuNJ0nm0mUEYgq9xMhYe3pIYxUxNvI3GjfZFGSR3QPOhzTfU8FooZOzO4+qCw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:14:46.485827Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.06280","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:07295e37f54ec3e686a949cecaeb77cd4c166cd92fe7bbb9c6fecbe9bb9c6377","sha256:918ed72ad6eb505566e7f8a86223352c289d395014f62d59cba127dd3f304a61"],"state_sha256":"6f3b7a27e73c74686bc7a771dd3ec9e3926a6023500edf4355df280e3ebe7f0c"}