{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:TVJUVZJ26KLXEZCSETPUOBOWZT","short_pith_number":"pith:TVJUVZJ2","canonical_record":{"source":{"id":"1707.03858","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-07-12T18:38:54Z","cross_cats_sorted":["math.IT","stat.ML"],"title_canon_sha256":"3b9a9eccaab172c5a71c96e07d10e0bd721e1b7e1db1bf5ec17b190704139619","abstract_canon_sha256":"326267bd965476198d493455ecaa67b0c1e1ba99aab4afb18229237e97881c17"},"schema_version":"1.0"},"canonical_sha256":"9d534ae53af29772645224df4705d6ccc88ca34978e87eac5248f4669a311b30","source":{"kind":"arxiv","id":"1707.03858","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03858","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03858v3","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03858","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"pith_short_12","alias_value":"TVJUVZJ26KLX","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TVJUVZJ26KLXEZCS","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TVJUVZJ2","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:TVJUVZJ26KLXEZCSETPUOBOWZT","target":"record","payload":{"canonical_record":{"source":{"id":"1707.03858","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-07-12T18:38:54Z","cross_cats_sorted":["math.IT","stat.ML"],"title_canon_sha256":"3b9a9eccaab172c5a71c96e07d10e0bd721e1b7e1db1bf5ec17b190704139619","abstract_canon_sha256":"326267bd965476198d493455ecaa67b0c1e1ba99aab4afb18229237e97881c17"},"schema_version":"1.0"},"canonical_sha256":"9d534ae53af29772645224df4705d6ccc88ca34978e87eac5248f4669a311b30","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:18.369584Z","signature_b64":"mvYASiyORK6+rZcr8HBHy15Bg25gnffI1RYbcGC0JEtEIvFj2yV4Q9o4OOxRI2paV3q9UZXwY0w8+sni0y3sBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9d534ae53af29772645224df4705d6ccc88ca34978e87eac5248f4669a311b30","last_reissued_at":"2026-05-17T23:41:18.368947Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:18.368947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.03858","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":"2026-05-17T23:41:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ydNW/XcgGkbkj4TDqSXzaT8/z7XAFn1REVUQyP5TPhwWnXnno7qH6H9wLZ/kOII3GKcrYhzyKW8JXWB/2mcpDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:35:33.694492Z"},"content_sha256":"7560123d59afa9d1fe9115659c18d814299b050a11d3e9181e3c70224018f222","schema_version":"1.0","event_id":"sha256:7560123d59afa9d1fe9115659c18d814299b050a11d3e9181e3c70224018f222"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:TVJUVZJ26KLXEZCSETPUOBOWZT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Gradient Coding from Cyclic MDS Codes and Expander Graphs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","stat.ML"],"primary_cat":"cs.IT","authors_text":"Alexandros G. Dimakis, Itzhak Tamo, Netanel Raviv, Rashish Tandon","submitted_at":"2017-07-12T18:38:54Z","abstract_excerpt":"Gradient coding is a technique for straggler mitigation in distributed learning. In this paper we design novel gradient codes using tools from classical coding theory, namely, cyclic MDS codes, which compare favorably with existing solutions, both in the applicable range of parameters and in the complexity of the involved algorithms. Second, we introduce an approximate variant of the gradient coding problem, in which we settle for approximate gradient computation instead of the exact one. This approach enables graceful degradation, i.e., the $\\ell_2$ error of the approximate gradient is a decr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03858","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":"2026-05-17T23:41:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EaLVAN+1Q9mfCVQz1RpW4zwVuXWtXnNbIp0qtd1wkKwSbRjPuYWKeDxQfdPnXgxnn9asvKIsYUozVLjfT2yYDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:35:33.694830Z"},"content_sha256":"66c15bd052de0647ee245555197064476a63d3f538ff567a2044ba6f7247333f","schema_version":"1.0","event_id":"sha256:66c15bd052de0647ee245555197064476a63d3f538ff567a2044ba6f7247333f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/bundle.json","state_url":"https://pith.science/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/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":"2026-06-01T21:35:33Z","links":{"resolver":"https://pith.science/pith/TVJUVZJ26KLXEZCSETPUOBOWZT","bundle":"https://pith.science/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/bundle.json","state":"https://pith.science/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TVJUVZJ26KLXEZCSETPUOBOWZT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TVJUVZJ26KLXEZCSETPUOBOWZT","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":"326267bd965476198d493455ecaa67b0c1e1ba99aab4afb18229237e97881c17","cross_cats_sorted":["math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-07-12T18:38:54Z","title_canon_sha256":"3b9a9eccaab172c5a71c96e07d10e0bd721e1b7e1db1bf5ec17b190704139619"},"schema_version":"1.0","source":{"id":"1707.03858","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03858","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03858v3","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03858","created_at":"2026-05-17T23:41:18Z"},{"alias_kind":"pith_short_12","alias_value":"TVJUVZJ26KLX","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TVJUVZJ26KLXEZCS","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TVJUVZJ2","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:66c15bd052de0647ee245555197064476a63d3f538ff567a2044ba6f7247333f","target":"graph","created_at":"2026-05-17T23:41:18Z","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":"Gradient coding is a technique for straggler mitigation in distributed learning. In this paper we design novel gradient codes using tools from classical coding theory, namely, cyclic MDS codes, which compare favorably with existing solutions, both in the applicable range of parameters and in the complexity of the involved algorithms. Second, we introduce an approximate variant of the gradient coding problem, in which we settle for approximate gradient computation instead of the exact one. This approach enables graceful degradation, i.e., the $\\ell_2$ error of the approximate gradient is a decr","authors_text":"Alexandros G. Dimakis, Itzhak Tamo, Netanel Raviv, Rashish Tandon","cross_cats":["math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-07-12T18:38:54Z","title":"Gradient Coding from Cyclic MDS Codes and Expander Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03858","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":"sha256:7560123d59afa9d1fe9115659c18d814299b050a11d3e9181e3c70224018f222","target":"record","created_at":"2026-05-17T23:41:18Z","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":"326267bd965476198d493455ecaa67b0c1e1ba99aab4afb18229237e97881c17","cross_cats_sorted":["math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-07-12T18:38:54Z","title_canon_sha256":"3b9a9eccaab172c5a71c96e07d10e0bd721e1b7e1db1bf5ec17b190704139619"},"schema_version":"1.0","source":{"id":"1707.03858","kind":"arxiv","version":3}},"canonical_sha256":"9d534ae53af29772645224df4705d6ccc88ca34978e87eac5248f4669a311b30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9d534ae53af29772645224df4705d6ccc88ca34978e87eac5248f4669a311b30","first_computed_at":"2026-05-17T23:41:18.368947Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:18.368947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mvYASiyORK6+rZcr8HBHy15Bg25gnffI1RYbcGC0JEtEIvFj2yV4Q9o4OOxRI2paV3q9UZXwY0w8+sni0y3sBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:18.369584Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.03858","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7560123d59afa9d1fe9115659c18d814299b050a11d3e9181e3c70224018f222","sha256:66c15bd052de0647ee245555197064476a63d3f538ff567a2044ba6f7247333f"],"state_sha256":"0dc3617cdfb8137cba06521012b342bcb8aa32fccfaa53b1beb8ac2128057c6a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oBSxHywk8I1V3dfTbDE7CP07hG+Kup3GP6uSHlxpGn9jlqXFFjJqBMrJW0EeRdix3cFFprg8E+Gon0fqxXIaDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T21:35:33.696614Z","bundle_sha256":"6a1d39b4dfe737029083ab9573e8fa7ba5cb278bdc03360d8d9f7c49d4f6d2eb"}}