{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:BAQCVKBLKCS4X3NKQMO3LI4VPJ","short_pith_number":"pith:BAQCVKBL","canonical_record":{"source":{"id":"1906.00506","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-06-03T00:00:25Z","cross_cats_sorted":[],"title_canon_sha256":"404bef330fd713174e5c3949760fdc0adae0b43d98f724334ee4318ac95feefa","abstract_canon_sha256":"ae1dfed31020cd9b3d862196c8901171e26a08103783b74455b1f62a03a3b27c"},"schema_version":"1.0"},"canonical_sha256":"08202aa82b50a5cbedaa831db5a3957a6343516bd302a99cb4d100196a5168fb","source":{"kind":"arxiv","id":"1906.00506","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.00506","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"arxiv_version","alias_value":"1906.00506v3","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.00506","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"pith_short_12","alias_value":"BAQCVKBLKCS4","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BAQCVKBLKCS4X3NK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BAQCVKBL","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:BAQCVKBLKCS4X3NKQMO3LI4VPJ","target":"record","payload":{"canonical_record":{"source":{"id":"1906.00506","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-06-03T00:00:25Z","cross_cats_sorted":[],"title_canon_sha256":"404bef330fd713174e5c3949760fdc0adae0b43d98f724334ee4318ac95feefa","abstract_canon_sha256":"ae1dfed31020cd9b3d862196c8901171e26a08103783b74455b1f62a03a3b27c"},"schema_version":"1.0"},"canonical_sha256":"08202aa82b50a5cbedaa831db5a3957a6343516bd302a99cb4d100196a5168fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:49.136918Z","signature_b64":"/m6aX0BC7qoBESKyYCxayDSTpCKR4Eb5fkbTt9L0pry1hXwjK1TbKcAIJFnWLKJ6NXnaD+PVhHB6N/Kf4CLVCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08202aa82b50a5cbedaa831db5a3957a6343516bd302a99cb4d100196a5168fb","last_reissued_at":"2026-05-17T23:43:49.136392Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:49.136392Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.00506","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":"2026-05-17T23:43:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kDYbGG433nwJLi9+cDgFDA53lKCiir7zAV+wCUOOm1ts7cyIo6I0hFCf+SO6yWOfqiIYR47aaGFAEEvNBzVIAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T03:14:50.437122Z"},"content_sha256":"e497225968b19c6b633b74dcdff06cbd0bc2cbaea6bbf08df62da5c7a4a0c191","schema_version":"1.0","event_id":"sha256:e497225968b19c6b633b74dcdff06cbd0bc2cbaea6bbf08df62da5c7a4a0c191"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:BAQCVKBLKCS4X3NKQMO3LI4VPJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Aryan Mokhtari, Konstantin Mischenko, Maryam Mehri Dehnavi, Mert Gurbuzbalaban, Saeed Soori","submitted_at":"2019-06-03T00:00:25Z","abstract_excerpt":"In this paper, we consider distributed algorithms for solving the empirical risk minimization problem under the master/worker communication model. We develop a distributed asynchronous quasi-Newton algorithm that can achieve superlinear convergence. To our knowledge, this is the first distributed asynchronous algorithm with superlinear convergence guarantees. Our algorithm is communication-efficient in the sense that at every iteration the master node and workers communicate vectors of size $O(p)$, where $p$ is the dimension of the decision variable. The proposed method is based on a distribut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.00506","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":"2026-05-17T23:43:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u7a4VcQs9MZlqoTiX3TOeUcTL4X4FXGxMBtyQdX/FEUwxT70BjZNlI1us7VvqFoJlQPhl3MuMFKyqiqsCPryCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T03:14:50.437810Z"},"content_sha256":"2e4331bb5b58971a8ec80a59b63656a3428df0faeeb9a3c7bf752b036a466555","schema_version":"1.0","event_id":"sha256:2e4331bb5b58971a8ec80a59b63656a3428df0faeeb9a3c7bf752b036a466555"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/bundle.json","state_url":"https://pith.science/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/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":"2026-05-22T03:14:50Z","links":{"resolver":"https://pith.science/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ","bundle":"https://pith.science/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/bundle.json","state":"https://pith.science/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BAQCVKBLKCS4X3NKQMO3LI4VPJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BAQCVKBLKCS4X3NKQMO3LI4VPJ","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":"ae1dfed31020cd9b3d862196c8901171e26a08103783b74455b1f62a03a3b27c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-06-03T00:00:25Z","title_canon_sha256":"404bef330fd713174e5c3949760fdc0adae0b43d98f724334ee4318ac95feefa"},"schema_version":"1.0","source":{"id":"1906.00506","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.00506","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"arxiv_version","alias_value":"1906.00506v3","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.00506","created_at":"2026-05-17T23:43:49Z"},{"alias_kind":"pith_short_12","alias_value":"BAQCVKBLKCS4","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BAQCVKBLKCS4X3NK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BAQCVKBL","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:2e4331bb5b58971a8ec80a59b63656a3428df0faeeb9a3c7bf752b036a466555","target":"graph","created_at":"2026-05-17T23:43:49Z","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":"In this paper, we consider distributed algorithms for solving the empirical risk minimization problem under the master/worker communication model. We develop a distributed asynchronous quasi-Newton algorithm that can achieve superlinear convergence. To our knowledge, this is the first distributed asynchronous algorithm with superlinear convergence guarantees. Our algorithm is communication-efficient in the sense that at every iteration the master node and workers communicate vectors of size $O(p)$, where $p$ is the dimension of the decision variable. The proposed method is based on a distribut","authors_text":"Aryan Mokhtari, Konstantin Mischenko, Maryam Mehri Dehnavi, Mert Gurbuzbalaban, Saeed Soori","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-06-03T00:00:25Z","title":"DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.00506","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:e497225968b19c6b633b74dcdff06cbd0bc2cbaea6bbf08df62da5c7a4a0c191","target":"record","created_at":"2026-05-17T23:43:49Z","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":"ae1dfed31020cd9b3d862196c8901171e26a08103783b74455b1f62a03a3b27c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-06-03T00:00:25Z","title_canon_sha256":"404bef330fd713174e5c3949760fdc0adae0b43d98f724334ee4318ac95feefa"},"schema_version":"1.0","source":{"id":"1906.00506","kind":"arxiv","version":3}},"canonical_sha256":"08202aa82b50a5cbedaa831db5a3957a6343516bd302a99cb4d100196a5168fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08202aa82b50a5cbedaa831db5a3957a6343516bd302a99cb4d100196a5168fb","first_computed_at":"2026-05-17T23:43:49.136392Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:43:49.136392Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/m6aX0BC7qoBESKyYCxayDSTpCKR4Eb5fkbTt9L0pry1hXwjK1TbKcAIJFnWLKJ6NXnaD+PVhHB6N/Kf4CLVCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:43:49.136918Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.00506","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e497225968b19c6b633b74dcdff06cbd0bc2cbaea6bbf08df62da5c7a4a0c191","sha256:2e4331bb5b58971a8ec80a59b63656a3428df0faeeb9a3c7bf752b036a466555"],"state_sha256":"941ffd96e8efb0e97d529c816f08b5331e0f475c6a33cabe2b49d54201d518e9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rghWV7LwmTYISnvjZLGQ/lY8Ige2C9BCgD0PN7VL6iwtvpeQJL05z6mkWTOSYJUuXUN7wmigpqTvUQCxzaHPCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T03:14:50.440984Z","bundle_sha256":"22fd2c91539607f5992193ea62d7c4003933edca626eb35ec0734c29109f5407"}}