{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OT5AZOKPIOVJGTIWIVVJ5XTOT7","short_pith_number":"pith:OT5AZOKP","canonical_record":{"source":{"id":"1805.10654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-27T17:02:26Z","cross_cats_sorted":["cs.SY","math.OC"],"title_canon_sha256":"23f9d400b334575cb438d0b98be251b358347730fb6089bcc22fe527e98e38e2","abstract_canon_sha256":"60ddaf3eca12181c2f711cbba668e16b0b6c1837b63892940c3870d44ddc26a3"},"schema_version":"1.0"},"canonical_sha256":"74fa0cb94f43aa934d16456a9ede6e9ffff888a9e88b04d341e3b2cd1d27a05e","source":{"kind":"arxiv","id":"1805.10654","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10654","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10654v1","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10654","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"pith_short_12","alias_value":"OT5AZOKPIOVJ","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OT5AZOKPIOVJGTIW","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OT5AZOKP","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OT5AZOKPIOVJGTIWIVVJ5XTOT7","target":"record","payload":{"canonical_record":{"source":{"id":"1805.10654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-27T17:02:26Z","cross_cats_sorted":["cs.SY","math.OC"],"title_canon_sha256":"23f9d400b334575cb438d0b98be251b358347730fb6089bcc22fe527e98e38e2","abstract_canon_sha256":"60ddaf3eca12181c2f711cbba668e16b0b6c1837b63892940c3870d44ddc26a3"},"schema_version":"1.0"},"canonical_sha256":"74fa0cb94f43aa934d16456a9ede6e9ffff888a9e88b04d341e3b2cd1d27a05e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:51.794707Z","signature_b64":"eYjkCaffkhuuGEurFB33UW2NtMaxxtwDIZn+nHy+mmyzs1ECen0BTaCIrqlipCYsFYaLg/PBqgtIKLcr0XCuBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74fa0cb94f43aa934d16456a9ede6e9ffff888a9e88b04d341e3b2cd1d27a05e","last_reissued_at":"2026-05-18T00:14:51.793989Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:51.793989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.10654","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r8KQJFKKggVHebHEcIW3dDbBt59zgH28ByOX+irskPVz764O3PNit1IBl7aYDPBz2JRO+7cz/lwKLVbbPXFtBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T19:06:22.001781Z"},"content_sha256":"9a2bbc4806071508dd5bf258bb5bb72ea47252915e33c5b855caaf4fed2fd218","schema_version":"1.0","event_id":"sha256:9a2bbc4806071508dd5bf258bb5bb72ea47252915e33c5b855caaf4fed2fd218"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OT5AZOKPIOVJGTIWIVVJ5XTOT7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Distributed Big-Data Optimization via Block Communications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","math.OC"],"primary_cat":"cs.DC","authors_text":"Gesualdo Scutari, Giuseppe Notarstefano, Ivano Notarnicola, Ying Sun","submitted_at":"2018-05-27T17:02:26Z","abstract_excerpt":"We study distributed multi-agent large-scale optimization problems, wherein the cost function is composed of a smooth possibly nonconvex sum-utility plus a DC (Difference-of-Convex) regularizer. We consider the scenario where the dimension of the optimization variables is so large that optimizing and/or transmitting the entire set of variables could cause unaffordable computation and communication overhead. To address this issue, we propose the first distributed algorithm whereby agents optimize and communicate only a portion of their local variables. The scheme hinges on successive convex app"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10654","kind":"arxiv","version":1},"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":"2026-05-18T00:14:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xsXUo0eI3vSpCFX9qSuK9zAXDes7ojW0suIw1eSQItzStvkt9o1FEfH9W0kmQoyYBaVJDcY/yEo2JDruhnizBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T19:06:22.002450Z"},"content_sha256":"4fc25b2a97b8ca60c2bbd6d5c6af955afa7aa1cfd11db0f8b454ca1c70173c8d","schema_version":"1.0","event_id":"sha256:4fc25b2a97b8ca60c2bbd6d5c6af955afa7aa1cfd11db0f8b454ca1c70173c8d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/bundle.json","state_url":"https://pith.science/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/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":"2026-06-08T19:06:22Z","links":{"resolver":"https://pith.science/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7","bundle":"https://pith.science/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/bundle.json","state":"https://pith.science/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OT5AZOKPIOVJGTIWIVVJ5XTOT7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OT5AZOKPIOVJGTIWIVVJ5XTOT7","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":"60ddaf3eca12181c2f711cbba668e16b0b6c1837b63892940c3870d44ddc26a3","cross_cats_sorted":["cs.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-27T17:02:26Z","title_canon_sha256":"23f9d400b334575cb438d0b98be251b358347730fb6089bcc22fe527e98e38e2"},"schema_version":"1.0","source":{"id":"1805.10654","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10654","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10654v1","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10654","created_at":"2026-05-18T00:14:51Z"},{"alias_kind":"pith_short_12","alias_value":"OT5AZOKPIOVJ","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OT5AZOKPIOVJGTIW","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OT5AZOKP","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:4fc25b2a97b8ca60c2bbd6d5c6af955afa7aa1cfd11db0f8b454ca1c70173c8d","target":"graph","created_at":"2026-05-18T00:14:51Z","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":"We study distributed multi-agent large-scale optimization problems, wherein the cost function is composed of a smooth possibly nonconvex sum-utility plus a DC (Difference-of-Convex) regularizer. We consider the scenario where the dimension of the optimization variables is so large that optimizing and/or transmitting the entire set of variables could cause unaffordable computation and communication overhead. To address this issue, we propose the first distributed algorithm whereby agents optimize and communicate only a portion of their local variables. The scheme hinges on successive convex app","authors_text":"Gesualdo Scutari, Giuseppe Notarstefano, Ivano Notarnicola, Ying Sun","cross_cats":["cs.SY","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-27T17:02:26Z","title":"Distributed Big-Data Optimization via Block Communications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10654","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":"sha256:9a2bbc4806071508dd5bf258bb5bb72ea47252915e33c5b855caaf4fed2fd218","target":"record","created_at":"2026-05-18T00:14:51Z","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":"60ddaf3eca12181c2f711cbba668e16b0b6c1837b63892940c3870d44ddc26a3","cross_cats_sorted":["cs.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2018-05-27T17:02:26Z","title_canon_sha256":"23f9d400b334575cb438d0b98be251b358347730fb6089bcc22fe527e98e38e2"},"schema_version":"1.0","source":{"id":"1805.10654","kind":"arxiv","version":1}},"canonical_sha256":"74fa0cb94f43aa934d16456a9ede6e9ffff888a9e88b04d341e3b2cd1d27a05e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74fa0cb94f43aa934d16456a9ede6e9ffff888a9e88b04d341e3b2cd1d27a05e","first_computed_at":"2026-05-18T00:14:51.793989Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:51.793989Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eYjkCaffkhuuGEurFB33UW2NtMaxxtwDIZn+nHy+mmyzs1ECen0BTaCIrqlipCYsFYaLg/PBqgtIKLcr0XCuBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:51.794707Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.10654","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a2bbc4806071508dd5bf258bb5bb72ea47252915e33c5b855caaf4fed2fd218","sha256:4fc25b2a97b8ca60c2bbd6d5c6af955afa7aa1cfd11db0f8b454ca1c70173c8d"],"state_sha256":"7e118e358d0b6364d66b2f461bc2f5eca5cacd0f3270a6eabe6d162c33f44b89"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"buZNyr6E7IkhV68CHJFle02WVJWg+AndzTuZucLqv1a7qOnFXM+j4iPFYlb7+9OuhF5gusR930mYjjs3JodbDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T19:06:22.006345Z","bundle_sha256":"f098017fde2c3891615e332e88eee0b4c34b14e14c705b002f3636d480db1c9e"}}