{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:E5LLZU6SR2E3NTSZX5XHDLDRGR","short_pith_number":"pith:E5LLZU6S","canonical_record":{"source":{"id":"2101.11203","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T04:38:27Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"65d066da27414e6b9262e27919a83e5544dda923260f68d62e411c0c4d8f28f4","abstract_canon_sha256":"e13470c20ed5aee4b437ef60c50b6fe82291492df9d7ee7b4071188541cf2977"},"schema_version":"1.0"},"canonical_sha256":"2756bcd3d28e89b6ce59bf6e71ac713457fc8b8c0a31557c38ee3861d670b6a6","source":{"kind":"arxiv","id":"2101.11203","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.11203","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"arxiv_version","alias_value":"2101.11203v3","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.11203","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_12","alias_value":"E5LLZU6SR2E3","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_16","alias_value":"E5LLZU6SR2E3NTSZ","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_8","alias_value":"E5LLZU6S","created_at":"2026-07-05T02:37:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:E5LLZU6SR2E3NTSZX5XHDLDRGR","target":"record","payload":{"canonical_record":{"source":{"id":"2101.11203","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T04:38:27Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"65d066da27414e6b9262e27919a83e5544dda923260f68d62e411c0c4d8f28f4","abstract_canon_sha256":"e13470c20ed5aee4b437ef60c50b6fe82291492df9d7ee7b4071188541cf2977"},"schema_version":"1.0"},"canonical_sha256":"2756bcd3d28e89b6ce59bf6e71ac713457fc8b8c0a31557c38ee3861d670b6a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:37:09.565853Z","signature_b64":"9ojbaqjMt+beqTdELFy7F8HwXCF9j2AwM7FX7O5DRoVr86OmXOO7NMlGUFZEVQRGtYKMiqmCgwXellI8N27eAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2756bcd3d28e89b6ce59bf6e71ac713457fc8b8c0a31557c38ee3861d670b6a6","last_reissued_at":"2026-07-05T02:37:09.565341Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:37:09.565341Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.11203","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:37:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"773ucNG7edSBgALnHhpFuU1qtZG9Cg17Mp0tTrmKHHVKHXYS1Z16mCJxt9V3WS5cbTd2rMe1ozDoGIK27Cn8Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:42:44.642648Z"},"content_sha256":"fca47a8ef2e2d952cd0837a0f867515723835bdfc2b978922a8c1e323a961d68","schema_version":"1.0","event_id":"sha256:fca47a8ef2e2d952cd0837a0f867515723835bdfc2b978922a8c1e323a961d68"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:E5LLZU6SR2E3NTSZX5XHDLDRGR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.LG","authors_text":"Haibo Yang, Jia Liu, Minghong Fang","submitted_at":"2021-01-27T04:38:27Z","abstract_excerpt":"Federated learning (FL) is a distributed machine learning architecture that leverages a large number of workers to jointly learn a model with decentralized data. FL has received increasing attention in recent years thanks to its data privacy protection, communication efficiency and a linear speedup for convergence in training (i.e., convergence performance increases linearly with respect to the number of workers). However, existing studies on linear speedup for convergence are only limited to the assumptions of i.i.d. datasets across workers and/or full worker participation, both of which rare"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.11203","kind":"arxiv","version":3},"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/2101.11203/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":"2026-07-05T02:37:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"algPbI+bTx6TY+5DrMQFCefAK+RGEFFwmZJzTbFzPjlhlRRY7Nj93xX7wNlkV9jlAmgxz1Vq4/Kpa6KEdpd/AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:42:44.643165Z"},"content_sha256":"7d55d58fb7c43df80c19f370a02ac0bd0f171d3931c91820c6515dc36afa60a3","schema_version":"1.0","event_id":"sha256:7d55d58fb7c43df80c19f370a02ac0bd0f171d3931c91820c6515dc36afa60a3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/bundle.json","state_url":"https://pith.science/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/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":"2026-08-06T03:42:44Z","links":{"resolver":"https://pith.science/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR","bundle":"https://pith.science/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/bundle.json","state":"https://pith.science/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E5LLZU6SR2E3NTSZX5XHDLDRGR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:E5LLZU6SR2E3NTSZX5XHDLDRGR","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":"e13470c20ed5aee4b437ef60c50b6fe82291492df9d7ee7b4071188541cf2977","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T04:38:27Z","title_canon_sha256":"65d066da27414e6b9262e27919a83e5544dda923260f68d62e411c0c4d8f28f4"},"schema_version":"1.0","source":{"id":"2101.11203","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.11203","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"arxiv_version","alias_value":"2101.11203v3","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.11203","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_12","alias_value":"E5LLZU6SR2E3","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_16","alias_value":"E5LLZU6SR2E3NTSZ","created_at":"2026-07-05T02:37:09Z"},{"alias_kind":"pith_short_8","alias_value":"E5LLZU6S","created_at":"2026-07-05T02:37:09Z"}],"graph_snapshots":[{"event_id":"sha256:7d55d58fb7c43df80c19f370a02ac0bd0f171d3931c91820c6515dc36afa60a3","target":"graph","created_at":"2026-07-05T02:37:09Z","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/2101.11203/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) is a distributed machine learning architecture that leverages a large number of workers to jointly learn a model with decentralized data. FL has received increasing attention in recent years thanks to its data privacy protection, communication efficiency and a linear speedup for convergence in training (i.e., convergence performance increases linearly with respect to the number of workers). However, existing studies on linear speedup for convergence are only limited to the assumptions of i.i.d. datasets across workers and/or full worker participation, both of which rare","authors_text":"Haibo Yang, Jia Liu, Minghong Fang","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T04:38:27Z","title":"Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.11203","kind":"arxiv","version":3},"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:fca47a8ef2e2d952cd0837a0f867515723835bdfc2b978922a8c1e323a961d68","target":"record","created_at":"2026-07-05T02:37:09Z","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":"e13470c20ed5aee4b437ef60c50b6fe82291492df9d7ee7b4071188541cf2977","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-01-27T04:38:27Z","title_canon_sha256":"65d066da27414e6b9262e27919a83e5544dda923260f68d62e411c0c4d8f28f4"},"schema_version":"1.0","source":{"id":"2101.11203","kind":"arxiv","version":3}},"canonical_sha256":"2756bcd3d28e89b6ce59bf6e71ac713457fc8b8c0a31557c38ee3861d670b6a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2756bcd3d28e89b6ce59bf6e71ac713457fc8b8c0a31557c38ee3861d670b6a6","first_computed_at":"2026-07-05T02:37:09.565341Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:37:09.565341Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9ojbaqjMt+beqTdELFy7F8HwXCF9j2AwM7FX7O5DRoVr86OmXOO7NMlGUFZEVQRGtYKMiqmCgwXellI8N27eAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:37:09.565853Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.11203","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fca47a8ef2e2d952cd0837a0f867515723835bdfc2b978922a8c1e323a961d68","sha256:7d55d58fb7c43df80c19f370a02ac0bd0f171d3931c91820c6515dc36afa60a3"],"state_sha256":"c19a46bfb4600b46e7b0c5590a9ced21560179a9746bce63c2bf7cf4d599f471"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cbm0qW6ICPH/urHXmuOFkH2N7iF/Md+XimY99i1mH/z8a6mCVwCbQeIPQUhhy30CJaQIilo++T21YgbBXD+uCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T03:42:44.648607Z","bundle_sha256":"f293626352a86936ab4cf9a9d0595f78f5649791e5238b5ad6750f6428543b26"}}