{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:ZHNVZCOG3XJOMPPVKCEBVGOB6W","short_pith_number":"pith:ZHNVZCOG","canonical_record":{"source":{"id":"1512.02673","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2015-12-08T21:54:04Z","cross_cats_sorted":["cs.IT","cs.LG","cs.PF","math.IT"],"title_canon_sha256":"d3ebfe8a5edf915289c86d6e93678ca5b870375d54de17448ee2b8d7fa31f5d0","abstract_canon_sha256":"b550252b0a82530529f2579e05e559a7acc8aef8be724b958574567cef99743a"},"schema_version":"1.0"},"canonical_sha256":"c9db5c89c6ddd2e63df550881a99c1f5b5f0675a695b46ae819dc90b34f31937","source":{"kind":"arxiv","id":"1512.02673","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.02673","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"1512.02673v3","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.02673","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"ZHNVZCOG3XJO","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"ZHNVZCOG3XJOMPPV","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"ZHNVZCOG","created_at":"2026-05-18T12:29:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:ZHNVZCOG3XJOMPPVKCEBVGOB6W","target":"record","payload":{"canonical_record":{"source":{"id":"1512.02673","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2015-12-08T21:54:04Z","cross_cats_sorted":["cs.IT","cs.LG","cs.PF","math.IT"],"title_canon_sha256":"d3ebfe8a5edf915289c86d6e93678ca5b870375d54de17448ee2b8d7fa31f5d0","abstract_canon_sha256":"b550252b0a82530529f2579e05e559a7acc8aef8be724b958574567cef99743a"},"schema_version":"1.0"},"canonical_sha256":"c9db5c89c6ddd2e63df550881a99c1f5b5f0675a695b46ae819dc90b34f31937","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:02.397534Z","signature_b64":"pg4dRaxqeAsNfZQA1t8Vax7Xp1EWempYH9geJFNnbVDhT0a/44zQ6WVFsMo8wPcLfHZuvRHzuebNSAxVh3P+AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9db5c89c6ddd2e63df550881a99c1f5b5f0675a695b46ae819dc90b34f31937","last_reissued_at":"2026-05-18T00:25:02.397152Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:02.397152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.02673","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":"2026-05-18T00:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zm7J1GaT5nsDC6sJ5rRZItTH+3RpprE0ikS+POao24x7CbFNc0e2WKpl40F0b7v95HpNqppmK2T4UV6ULw0DDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T18:58:55.723547Z"},"content_sha256":"b13133222c029079c8d5cbb9f0c6e25fdc45a447e1d42d51cb3730997e983ea4","schema_version":"1.0","event_id":"sha256:b13133222c029079c8d5cbb9f0c6e25fdc45a447e1d42d51cb3730997e983ea4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:ZHNVZCOG3XJOMPPVKCEBVGOB6W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Speeding Up Distributed Machine Learning Using Codes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","cs.PF","math.IT"],"primary_cat":"cs.DC","authors_text":"Dimitris Papailiopoulos, Kangwook Lee, Kannan Ramchandran, Maximilian Lam, Ramtin Pedarsani","submitted_at":"2015-12-08T21:54:04Z","abstract_excerpt":"Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems there are several types of noise that can affect the performance of distributed machine learning algorithms -- straggler nodes, system failures, or communication bottlenecks -- but there has been little interaction cutting across codes, machine learning, and distributed systems. In this work, we provide theoretical insights on how coded solutions can achieve significant gains compared to uncoded ones. We focus on two of the most basic building blocks of distributed learning algorith"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.02673","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":""},"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":"2026-05-18T00:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MwCu27f/XL8cvOAuRabbShyAIz4Zo6UZ9zMJQgbKFilhkdQpTudUvfrprwkIs59cAmGvcyEAy4up4zI2bnEyCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T18:58:55.723904Z"},"content_sha256":"3ec8c1b355f633f215c90fa5bc42cb2bfeeadf855557f1b07163ac0055002d06","schema_version":"1.0","event_id":"sha256:3ec8c1b355f633f215c90fa5bc42cb2bfeeadf855557f1b07163ac0055002d06"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/bundle.json","state_url":"https://pith.science/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/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":"2026-05-21T18:58:55Z","links":{"resolver":"https://pith.science/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W","bundle":"https://pith.science/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/bundle.json","state":"https://pith.science/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZHNVZCOG3XJOMPPVKCEBVGOB6W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:ZHNVZCOG3XJOMPPVKCEBVGOB6W","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":"b550252b0a82530529f2579e05e559a7acc8aef8be724b958574567cef99743a","cross_cats_sorted":["cs.IT","cs.LG","cs.PF","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2015-12-08T21:54:04Z","title_canon_sha256":"d3ebfe8a5edf915289c86d6e93678ca5b870375d54de17448ee2b8d7fa31f5d0"},"schema_version":"1.0","source":{"id":"1512.02673","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.02673","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"1512.02673v3","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.02673","created_at":"2026-05-18T00:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"ZHNVZCOG3XJO","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"ZHNVZCOG3XJOMPPV","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"ZHNVZCOG","created_at":"2026-05-18T12:29:52Z"}],"graph_snapshots":[{"event_id":"sha256:3ec8c1b355f633f215c90fa5bc42cb2bfeeadf855557f1b07163ac0055002d06","target":"graph","created_at":"2026-05-18T00:25:02Z","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"},"paper":{"abstract_excerpt":"Codes are widely used in many engineering applications to offer robustness against noise. In large-scale systems there are several types of noise that can affect the performance of distributed machine learning algorithms -- straggler nodes, system failures, or communication bottlenecks -- but there has been little interaction cutting across codes, machine learning, and distributed systems. In this work, we provide theoretical insights on how coded solutions can achieve significant gains compared to uncoded ones. We focus on two of the most basic building blocks of distributed learning algorith","authors_text":"Dimitris Papailiopoulos, Kangwook Lee, Kannan Ramchandran, Maximilian Lam, Ramtin Pedarsani","cross_cats":["cs.IT","cs.LG","cs.PF","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2015-12-08T21:54:04Z","title":"Speeding Up Distributed Machine Learning Using Codes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.02673","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:b13133222c029079c8d5cbb9f0c6e25fdc45a447e1d42d51cb3730997e983ea4","target":"record","created_at":"2026-05-18T00:25:02Z","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":"b550252b0a82530529f2579e05e559a7acc8aef8be724b958574567cef99743a","cross_cats_sorted":["cs.IT","cs.LG","cs.PF","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2015-12-08T21:54:04Z","title_canon_sha256":"d3ebfe8a5edf915289c86d6e93678ca5b870375d54de17448ee2b8d7fa31f5d0"},"schema_version":"1.0","source":{"id":"1512.02673","kind":"arxiv","version":3}},"canonical_sha256":"c9db5c89c6ddd2e63df550881a99c1f5b5f0675a695b46ae819dc90b34f31937","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9db5c89c6ddd2e63df550881a99c1f5b5f0675a695b46ae819dc90b34f31937","first_computed_at":"2026-05-18T00:25:02.397152Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:02.397152Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pg4dRaxqeAsNfZQA1t8Vax7Xp1EWempYH9geJFNnbVDhT0a/44zQ6WVFsMo8wPcLfHZuvRHzuebNSAxVh3P+AA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:02.397534Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.02673","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b13133222c029079c8d5cbb9f0c6e25fdc45a447e1d42d51cb3730997e983ea4","sha256:3ec8c1b355f633f215c90fa5bc42cb2bfeeadf855557f1b07163ac0055002d06"],"state_sha256":"e965246159c410b7e81ed918313da72643b194ca139293f14d37c27918c8e884"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AAaslwcQMhK1ytD5/KgavTQczRqTehzxCQ54/7BqN5v4j4LrxtCPcdxoAILxfhShSVmdkg5893fN8uxAoZslBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T18:58:55.729618Z","bundle_sha256":"6d1721394d76590db065d622d89041ffdfb4a2ecc865c440394f94566aeef5ae"}}