{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GP3P6AEXMOJ63KQTKHABPW6JO5","short_pith_number":"pith:GP3P6AEX","canonical_record":{"source":{"id":"1806.02617","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-07T11:20:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6d31bdcd6db297a2ad91a27272d4c262898dc95aa0e7f18b245bc24fedc62f45","abstract_canon_sha256":"9b5530e3d42a1ec865b46a6a87b4de92f03fea2139397aa0940695f4232cee37"},"schema_version":"1.0"},"canonical_sha256":"33f6ff00976393edaa1351c017dbc97740df363719d413920002838df28000be","source":{"kind":"arxiv","id":"1806.02617","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02617","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02617v1","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02617","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"pith_short_12","alias_value":"GP3P6AEXMOJ6","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GP3P6AEXMOJ63KQT","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GP3P6AEX","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GP3P6AEXMOJ63KQTKHABPW6JO5","target":"record","payload":{"canonical_record":{"source":{"id":"1806.02617","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-07T11:20:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6d31bdcd6db297a2ad91a27272d4c262898dc95aa0e7f18b245bc24fedc62f45","abstract_canon_sha256":"9b5530e3d42a1ec865b46a6a87b4de92f03fea2139397aa0940695f4232cee37"},"schema_version":"1.0"},"canonical_sha256":"33f6ff00976393edaa1351c017dbc97740df363719d413920002838df28000be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:56.259273Z","signature_b64":"uKBtCYOgqGKEfGoTMR+VZn3Lo4QA6ih7YCfUX54COXTwClpgRI+tvmEMzk+KmWzGMh6+yTPlf65Afjsc7Fm1CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"33f6ff00976393edaa1351c017dbc97740df363719d413920002838df28000be","last_reissued_at":"2026-05-18T00:13:56.258546Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:56.258546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.02617","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":"2026-05-18T00:13:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qNy1AB8mHFxSoohK/Q0VAx/0piQAi4tCv3CGhrX72gP3prQhTkdZEd8N+L9T4G8OAadJzQAQa2eKkwsiM9ShCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T20:42:13.125654Z"},"content_sha256":"b82803e09644a32842c445d565a45b9da7d301a45b36af77b9ff802705ccd0f7","schema_version":"1.0","event_id":"sha256:b82803e09644a32842c445d565a45b9da7d301a45b36af77b9ff802705ccd0f7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GP3P6AEXMOJ63KQTKHABPW6JO5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"A. Taylan Cemgil, \\c{C}a\\u{g}atay Y{\\i}ld{\\i}z, Ga\\\"el Richard, Thanh Huy Nguyen, Umut \\c{S}im\\c{s}ekli","submitted_at":"2018-06-07T11:20:10Z","abstract_excerpt":"Recent studies have illustrated that stochastic gradient Markov Chain Monte Carlo techniques have a strong potential in non-convex optimization, where local and global convergence guarantees can be shown under certain conditions. By building up on this recent theory, in this study, we develop an asynchronous-parallel stochastic L-BFGS algorithm for non-convex optimization. The proposed algorithm is suitable for both distributed and shared-memory settings. We provide formal theoretical analysis and show that the proposed method achieves an ergodic convergence rate of ${\\cal O}(1/\\sqrt{N})$ ($N$"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02617","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":"2026-05-18T00:13:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l2w6stL8iSKDwI8ArRArHRwMSIqOpcMZdBzXQMLwQzQCc8zArlo+cFA6VKMNcTMPJ4HKa1t9nCmMYiUMeQPhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T20:42:13.126266Z"},"content_sha256":"a975ff3e3f6ab5bb99fbcfc6e9b1a1e054a69f1dc63820901c0c292ac4ecd2da","schema_version":"1.0","event_id":"sha256:a975ff3e3f6ab5bb99fbcfc6e9b1a1e054a69f1dc63820901c0c292ac4ecd2da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/bundle.json","state_url":"https://pith.science/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/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":"2026-05-26T20:42:13Z","links":{"resolver":"https://pith.science/pith/GP3P6AEXMOJ63KQTKHABPW6JO5","bundle":"https://pith.science/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/bundle.json","state":"https://pith.science/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GP3P6AEXMOJ63KQTKHABPW6JO5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GP3P6AEXMOJ63KQTKHABPW6JO5","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":"9b5530e3d42a1ec865b46a6a87b4de92f03fea2139397aa0940695f4232cee37","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-07T11:20:10Z","title_canon_sha256":"6d31bdcd6db297a2ad91a27272d4c262898dc95aa0e7f18b245bc24fedc62f45"},"schema_version":"1.0","source":{"id":"1806.02617","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02617","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02617v1","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02617","created_at":"2026-05-18T00:13:56Z"},{"alias_kind":"pith_short_12","alias_value":"GP3P6AEXMOJ6","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GP3P6AEXMOJ63KQT","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GP3P6AEX","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:a975ff3e3f6ab5bb99fbcfc6e9b1a1e054a69f1dc63820901c0c292ac4ecd2da","target":"graph","created_at":"2026-05-18T00:13:56Z","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":"Recent studies have illustrated that stochastic gradient Markov Chain Monte Carlo techniques have a strong potential in non-convex optimization, where local and global convergence guarantees can be shown under certain conditions. By building up on this recent theory, in this study, we develop an asynchronous-parallel stochastic L-BFGS algorithm for non-convex optimization. The proposed algorithm is suitable for both distributed and shared-memory settings. We provide formal theoretical analysis and show that the proposed method achieves an ergodic convergence rate of ${\\cal O}(1/\\sqrt{N})$ ($N$","authors_text":"A. Taylan Cemgil, \\c{C}a\\u{g}atay Y{\\i}ld{\\i}z, Ga\\\"el Richard, Thanh Huy Nguyen, Umut \\c{S}im\\c{s}ekli","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-07T11:20:10Z","title":"Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02617","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:b82803e09644a32842c445d565a45b9da7d301a45b36af77b9ff802705ccd0f7","target":"record","created_at":"2026-05-18T00:13:56Z","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":"9b5530e3d42a1ec865b46a6a87b4de92f03fea2139397aa0940695f4232cee37","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-06-07T11:20:10Z","title_canon_sha256":"6d31bdcd6db297a2ad91a27272d4c262898dc95aa0e7f18b245bc24fedc62f45"},"schema_version":"1.0","source":{"id":"1806.02617","kind":"arxiv","version":1}},"canonical_sha256":"33f6ff00976393edaa1351c017dbc97740df363719d413920002838df28000be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"33f6ff00976393edaa1351c017dbc97740df363719d413920002838df28000be","first_computed_at":"2026-05-18T00:13:56.258546Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:56.258546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uKBtCYOgqGKEfGoTMR+VZn3Lo4QA6ih7YCfUX54COXTwClpgRI+tvmEMzk+KmWzGMh6+yTPlf65Afjsc7Fm1CQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:56.259273Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.02617","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b82803e09644a32842c445d565a45b9da7d301a45b36af77b9ff802705ccd0f7","sha256:a975ff3e3f6ab5bb99fbcfc6e9b1a1e054a69f1dc63820901c0c292ac4ecd2da"],"state_sha256":"229dc6a32ea796df6de3cff93856d6b501a538438ed888b1697e3785c216860d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lXyE09YLvdRvl1G/477EHAhRwd4Jh8D31iz6sFlJpthothr0hplcuh7seoIZ9w4sVJIDZ7kpKnvR0LY/iEQKAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T20:42:13.129687Z","bundle_sha256":"0a0a0f5184b82c182df1912f570e21161f2dd168f1f90b63aba7c1bfee41cedb"}}