{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:HNJSFZ2BL26VFWBTGJUB6E6GTJ","short_pith_number":"pith:HNJSFZ2B","schema_version":"1.0","canonical_sha256":"3b5322e7415ebd52d83332681f13c69a59891a32613088110e9ea1bb2bbfc55a","source":{"kind":"arxiv","id":"1711.04969","version":2},"attestation_state":"computed","paper":{"title":"Straggler Mitigation in Distributed Optimization Through Data Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.IT","cs.LG","math.IT"],"primary_cat":"stat.ML","authors_text":"Can Karakus, Suhas Diggavi, Wotao Yin, Yifan Sun","submitted_at":"2017-11-14T06:29:41Z","abstract_excerpt":"Slow running or straggler tasks can significantly reduce computation speed in distributed computation. Recently, coding-theory-inspired approaches have been applied to mitigate the effect of straggling, through embedding redundancy in certain linear computational steps of the optimization algorithm, thus completing the computation without waiting for the stragglers. In this paper, we propose an alternate approach where we embed the redundancy directly in the data itself, and allow the computation to proceed completely oblivious to encoding. We propose several encoding schemes, and demonstrate "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1711.04969","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-14T06:29:41Z","cross_cats_sorted":["cs.DC","cs.IT","cs.LG","math.IT"],"title_canon_sha256":"35ad8c49c9d9d6a196f36a5c569a1238928ede764e95e5afdeeff15112b7713f","abstract_canon_sha256":"79c9966e40976bca166cc1359a8201f4e118fe37603ee3ef1501be73010fde09"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:16.202013Z","signature_b64":"1aZcOR2MFhC2czuJyTncjVd7ewHoumbt4MoFkwRSx+nFRIVBIndSfr7/AbPWVJYWKkqErsqyc9F5wFTj/BMUDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b5322e7415ebd52d83332681f13c69a59891a32613088110e9ea1bb2bbfc55a","last_reissued_at":"2026-05-18T00:25:16.201441Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:16.201441Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Straggler Mitigation in Distributed Optimization Through Data Encoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.IT","cs.LG","math.IT"],"primary_cat":"stat.ML","authors_text":"Can Karakus, Suhas Diggavi, Wotao Yin, Yifan Sun","submitted_at":"2017-11-14T06:29:41Z","abstract_excerpt":"Slow running or straggler tasks can significantly reduce computation speed in distributed computation. Recently, coding-theory-inspired approaches have been applied to mitigate the effect of straggling, through embedding redundancy in certain linear computational steps of the optimization algorithm, thus completing the computation without waiting for the stragglers. In this paper, we propose an alternate approach where we embed the redundancy directly in the data itself, and allow the computation to proceed completely oblivious to encoding. We propose several encoding schemes, and demonstrate "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.04969","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1711.04969","created_at":"2026-05-18T00:25:16.201538+00:00"},{"alias_kind":"arxiv_version","alias_value":"1711.04969v2","created_at":"2026-05-18T00:25:16.201538+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.04969","created_at":"2026-05-18T00:25:16.201538+00:00"},{"alias_kind":"pith_short_12","alias_value":"HNJSFZ2BL26V","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_16","alias_value":"HNJSFZ2BL26VFWBT","created_at":"2026-05-18T12:31:18.294218+00:00"},{"alias_kind":"pith_short_8","alias_value":"HNJSFZ2B","created_at":"2026-05-18T12:31:18.294218+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ","json":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ.json","graph_json":"https://pith.science/api/pith-number/HNJSFZ2BL26VFWBTGJUB6E6GTJ/graph.json","events_json":"https://pith.science/api/pith-number/HNJSFZ2BL26VFWBTGJUB6E6GTJ/events.json","paper":"https://pith.science/paper/HNJSFZ2B"},"agent_actions":{"view_html":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ","download_json":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ.json","view_paper":"https://pith.science/paper/HNJSFZ2B","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1711.04969&json=true","fetch_graph":"https://pith.science/api/pith-number/HNJSFZ2BL26VFWBTGJUB6E6GTJ/graph.json","fetch_events":"https://pith.science/api/pith-number/HNJSFZ2BL26VFWBTGJUB6E6GTJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ/action/storage_attestation","attest_author":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ/action/author_attestation","sign_citation":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ/action/citation_signature","submit_replication":"https://pith.science/pith/HNJSFZ2BL26VFWBTGJUB6E6GTJ/action/replication_record"}},"created_at":"2026-05-18T00:25:16.201538+00:00","updated_at":"2026-05-18T00:25:16.201538+00:00"}