{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:P6K6YCAV5CE65ANQHGJTMMX3IM","short_pith_number":"pith:P6K6YCAV","canonical_record":{"source":{"id":"1709.01427","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-05T14:50:55Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"391a854e18341d16d763cef5b4d33c8d270ac8429824e1db19a9c251be446aaa","abstract_canon_sha256":"f00a263ff84083373bd3730a3362cf9fc9ca125740fef30d60f495175453bc19"},"schema_version":"1.0"},"canonical_sha256":"7f95ec0815e889ee81b039933632fb43112072a29f96e28bd07855ae07a124a9","source":{"kind":"arxiv","id":"1709.01427","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.01427","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"arxiv_version","alias_value":"1709.01427v1","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.01427","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"pith_short_12","alias_value":"P6K6YCAV5CE6","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P6K6YCAV5CE65ANQ","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P6K6YCAV","created_at":"2026-05-18T12:31:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:P6K6YCAV5CE65ANQHGJTMMX3IM","target":"record","payload":{"canonical_record":{"source":{"id":"1709.01427","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-05T14:50:55Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"391a854e18341d16d763cef5b4d33c8d270ac8429824e1db19a9c251be446aaa","abstract_canon_sha256":"f00a263ff84083373bd3730a3362cf9fc9ca125740fef30d60f495175453bc19"},"schema_version":"1.0"},"canonical_sha256":"7f95ec0815e889ee81b039933632fb43112072a29f96e28bd07855ae07a124a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:36:00.138128Z","signature_b64":"rnCtGH97VCJKh56tkdahJk0ozgNoOU5nF9PfeKGOYyLKnVZ0f0C7R1FDyUqvNdtovZSK5D/DSUR/DSbOf/zDAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f95ec0815e889ee81b039933632fb43112072a29f96e28bd07855ae07a124a9","last_reissued_at":"2026-05-18T00:36:00.137640Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:36:00.137640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.01427","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":"2026-05-18T00:36:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MyqaRMTPkzsoZ7e+ZRHuiCM7Q1LKl972ZOqvEn3nYRBpB6RLNmVMcHp8wPG5R337Jo/tnbIxlYgdGSVYhCg6DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:27:54.456799Z"},"content_sha256":"8501bf38fda73e39dc227aa047b664f0146b2d6e5d3742b2295dd3e55fb62bd3","schema_version":"1.0","event_id":"sha256:8501bf38fda73e39dc227aa047b664f0146b2d6e5d3742b2295dd3e55fb62bd3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:P6K6YCAV5CE65ANQHGJTMMX3IM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Stochastic Gradient Descent: Going As Fast As Possible But Not Faster","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"stat.ML","authors_text":"Alice Schoenauer-Sebag, Marc Schoenauer, Mich\\`ele Sebag","submitted_at":"2017-09-05T14:50:55Z","abstract_excerpt":"When applied to training deep neural networks, stochastic gradient descent (SGD) often incurs steady progression phases, interrupted by catastrophic episodes in which loss and gradient norm explode. A possible mitigation of such events is to slow down the learning process. This paper presents a novel approach to control the SGD learning rate, that uses two statistical tests. The first one, aimed at fast learning, compares the momentum of the normalized gradient vectors to that of random unit vectors and accordingly gracefully increases or decreases the learning rate. The second one is a change"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.01427","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":"2026-05-18T00:36:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nlt/BhifcvHDLWAIfaGSSU2kccqiAHSbt1NB+UlcmP+jljG6UnP7ThCRtFzK4us31kpS0MHdG9T3m0Ky95WNCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:27:54.457578Z"},"content_sha256":"29e03c1f5a8828102f8898406ac49f00830e2efb53b922195a27315f492dc9b6","schema_version":"1.0","event_id":"sha256:29e03c1f5a8828102f8898406ac49f00830e2efb53b922195a27315f492dc9b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/bundle.json","state_url":"https://pith.science/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/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":"2026-06-11T21:27:54Z","links":{"resolver":"https://pith.science/pith/P6K6YCAV5CE65ANQHGJTMMX3IM","bundle":"https://pith.science/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/bundle.json","state":"https://pith.science/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P6K6YCAV5CE65ANQHGJTMMX3IM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:P6K6YCAV5CE65ANQHGJTMMX3IM","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":"f00a263ff84083373bd3730a3362cf9fc9ca125740fef30d60f495175453bc19","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-05T14:50:55Z","title_canon_sha256":"391a854e18341d16d763cef5b4d33c8d270ac8429824e1db19a9c251be446aaa"},"schema_version":"1.0","source":{"id":"1709.01427","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.01427","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"arxiv_version","alias_value":"1709.01427v1","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.01427","created_at":"2026-05-18T00:36:00Z"},{"alias_kind":"pith_short_12","alias_value":"P6K6YCAV5CE6","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"P6K6YCAV5CE65ANQ","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"P6K6YCAV","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:29e03c1f5a8828102f8898406ac49f00830e2efb53b922195a27315f492dc9b6","target":"graph","created_at":"2026-05-18T00:36:00Z","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":"When applied to training deep neural networks, stochastic gradient descent (SGD) often incurs steady progression phases, interrupted by catastrophic episodes in which loss and gradient norm explode. A possible mitigation of such events is to slow down the learning process. This paper presents a novel approach to control the SGD learning rate, that uses two statistical tests. The first one, aimed at fast learning, compares the momentum of the normalized gradient vectors to that of random unit vectors and accordingly gracefully increases or decreases the learning rate. The second one is a change","authors_text":"Alice Schoenauer-Sebag, Marc Schoenauer, Mich\\`ele Sebag","cross_cats":["cs.LG","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-05T14:50:55Z","title":"Stochastic Gradient Descent: Going As Fast As Possible But Not Faster"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.01427","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":"sha256:8501bf38fda73e39dc227aa047b664f0146b2d6e5d3742b2295dd3e55fb62bd3","target":"record","created_at":"2026-05-18T00:36:00Z","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":"f00a263ff84083373bd3730a3362cf9fc9ca125740fef30d60f495175453bc19","cross_cats_sorted":["cs.LG","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-09-05T14:50:55Z","title_canon_sha256":"391a854e18341d16d763cef5b4d33c8d270ac8429824e1db19a9c251be446aaa"},"schema_version":"1.0","source":{"id":"1709.01427","kind":"arxiv","version":1}},"canonical_sha256":"7f95ec0815e889ee81b039933632fb43112072a29f96e28bd07855ae07a124a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f95ec0815e889ee81b039933632fb43112072a29f96e28bd07855ae07a124a9","first_computed_at":"2026-05-18T00:36:00.137640Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:36:00.137640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rnCtGH97VCJKh56tkdahJk0ozgNoOU5nF9PfeKGOYyLKnVZ0f0C7R1FDyUqvNdtovZSK5D/DSUR/DSbOf/zDAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:36:00.138128Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.01427","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8501bf38fda73e39dc227aa047b664f0146b2d6e5d3742b2295dd3e55fb62bd3","sha256:29e03c1f5a8828102f8898406ac49f00830e2efb53b922195a27315f492dc9b6"],"state_sha256":"394cd7cca0a4098b40b7feecf8aa29b1f3b32922987bf656423ae913565b750a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uPCyg8b/54Aze3WTemmInc9yp7W5L+UH2vkEAoNl6OVRTTCkZE3p8crTo0/K/LZGjK/g1LMf30XKgIm3WnS9Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T21:27:54.460613Z","bundle_sha256":"a603728008c3538df1fd4ff9ff63b8ca5d2bbd032fe23a905a11df757adcb5f3"}}