{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:VYY7OERQJDB7HB6AWVJJ73VD4W","short_pith_number":"pith:VYY7OERQ","canonical_record":{"source":{"id":"1312.6055","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-20T17:44:06Z","cross_cats_sorted":[],"title_canon_sha256":"fa4708c9f0a7825b054dc4a168cc9da80c0d7899ba83db643908ad3bd94841b9","abstract_canon_sha256":"606121296868352b26c0ea696a27167b52b9b53a31db27a606013ffb447654e3"},"schema_version":"1.0"},"canonical_sha256":"ae31f7123048c3f387c0b5529feea3e58d196d1d3c37a006fdc20a8b18cdb829","source":{"kind":"arxiv","id":"1312.6055","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.6055","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"arxiv_version","alias_value":"1312.6055v3","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.6055","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"pith_short_12","alias_value":"VYY7OERQJDB7","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_16","alias_value":"VYY7OERQJDB7HB6A","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_8","alias_value":"VYY7OERQ","created_at":"2026-05-18T12:28:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:VYY7OERQJDB7HB6AWVJJ73VD4W","target":"record","payload":{"canonical_record":{"source":{"id":"1312.6055","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-20T17:44:06Z","cross_cats_sorted":[],"title_canon_sha256":"fa4708c9f0a7825b054dc4a168cc9da80c0d7899ba83db643908ad3bd94841b9","abstract_canon_sha256":"606121296868352b26c0ea696a27167b52b9b53a31db27a606013ffb447654e3"},"schema_version":"1.0"},"canonical_sha256":"ae31f7123048c3f387c0b5529feea3e58d196d1d3c37a006fdc20a8b18cdb829","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:57:52.156109Z","signature_b64":"KZc8AvXBBcOLjy3u9YRJDFJl8wr1WghShJ7CqYx0EaYcqwccAYqAf+y/erNbbMcXgQv8kyGu6EVaVgfP1S9ABQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae31f7123048c3f387c0b5529feea3e58d196d1d3c37a006fdc20a8b18cdb829","last_reissued_at":"2026-05-18T02:57:52.155537Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:57:52.155537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1312.6055","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":"2026-05-18T02:57:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ygXT7CdG+Wl7Zbp+N8fBIAAbOglvlS+t8Wh7aDeCVkaYQqACm7xSabqMj8SeTFH3RcBLPEgWYZEo9jUroc+rDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T23:38:44.281311Z"},"content_sha256":"b7986d38a0dcab2c5ae99d6557d683e4d51267744f4d21eeae1a7c32d04b966f","schema_version":"1.0","event_id":"sha256:b7986d38a0dcab2c5ae99d6557d683e4d51267744f4d21eeae1a7c32d04b966f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:VYY7OERQJDB7HB6AWVJJ73VD4W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unit Tests for Stochastic Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"David Silver, Ioannis Antonoglou, Tom Schaul","submitted_at":"2013-12-20T17:44:06Z","abstract_excerpt":"Optimization by stochastic gradient descent is an important component of many large-scale machine learning algorithms. A wide variety of such optimization algorithms have been devised; however, it is unclear whether these algorithms are robust and widely applicable across many different optimization landscapes. In this paper we develop a collection of unit tests for stochastic optimization. Each unit test rapidly evaluates an optimization algorithm on a small-scale, isolated, and well-understood difficulty, rather than in real-world scenarios where many such issues are entangled. Passing these"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.6055","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":"2026-05-18T02:57:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WUxO9+1dUMvgbfp+JKNEWYW9lo7/D0itnLDAob+wCa9fLCl+pgirf++pe8xTpMwzlVxzLca1Rqv9xh0X88HaCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T23:38:44.281676Z"},"content_sha256":"b23b8957f38d6cd94026945ad6189f60769ba246065ad9df7b13a499a00c8b8a","schema_version":"1.0","event_id":"sha256:b23b8957f38d6cd94026945ad6189f60769ba246065ad9df7b13a499a00c8b8a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/bundle.json","state_url":"https://pith.science/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/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":"2026-06-01T23:38:44Z","links":{"resolver":"https://pith.science/pith/VYY7OERQJDB7HB6AWVJJ73VD4W","bundle":"https://pith.science/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/bundle.json","state":"https://pith.science/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VYY7OERQJDB7HB6AWVJJ73VD4W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:VYY7OERQJDB7HB6AWVJJ73VD4W","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":"606121296868352b26c0ea696a27167b52b9b53a31db27a606013ffb447654e3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-20T17:44:06Z","title_canon_sha256":"fa4708c9f0a7825b054dc4a168cc9da80c0d7899ba83db643908ad3bd94841b9"},"schema_version":"1.0","source":{"id":"1312.6055","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.6055","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"arxiv_version","alias_value":"1312.6055v3","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.6055","created_at":"2026-05-18T02:57:52Z"},{"alias_kind":"pith_short_12","alias_value":"VYY7OERQJDB7","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_16","alias_value":"VYY7OERQJDB7HB6A","created_at":"2026-05-18T12:28:04Z"},{"alias_kind":"pith_short_8","alias_value":"VYY7OERQ","created_at":"2026-05-18T12:28:04Z"}],"graph_snapshots":[{"event_id":"sha256:b23b8957f38d6cd94026945ad6189f60769ba246065ad9df7b13a499a00c8b8a","target":"graph","created_at":"2026-05-18T02:57:52Z","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":"Optimization by stochastic gradient descent is an important component of many large-scale machine learning algorithms. A wide variety of such optimization algorithms have been devised; however, it is unclear whether these algorithms are robust and widely applicable across many different optimization landscapes. In this paper we develop a collection of unit tests for stochastic optimization. Each unit test rapidly evaluates an optimization algorithm on a small-scale, isolated, and well-understood difficulty, rather than in real-world scenarios where many such issues are entangled. Passing these","authors_text":"David Silver, Ioannis Antonoglou, Tom Schaul","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-20T17:44:06Z","title":"Unit Tests for Stochastic Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.6055","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:b7986d38a0dcab2c5ae99d6557d683e4d51267744f4d21eeae1a7c32d04b966f","target":"record","created_at":"2026-05-18T02:57:52Z","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":"606121296868352b26c0ea696a27167b52b9b53a31db27a606013ffb447654e3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-20T17:44:06Z","title_canon_sha256":"fa4708c9f0a7825b054dc4a168cc9da80c0d7899ba83db643908ad3bd94841b9"},"schema_version":"1.0","source":{"id":"1312.6055","kind":"arxiv","version":3}},"canonical_sha256":"ae31f7123048c3f387c0b5529feea3e58d196d1d3c37a006fdc20a8b18cdb829","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae31f7123048c3f387c0b5529feea3e58d196d1d3c37a006fdc20a8b18cdb829","first_computed_at":"2026-05-18T02:57:52.155537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:57:52.155537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KZc8AvXBBcOLjy3u9YRJDFJl8wr1WghShJ7CqYx0EaYcqwccAYqAf+y/erNbbMcXgQv8kyGu6EVaVgfP1S9ABQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:57:52.156109Z","signed_message":"canonical_sha256_bytes"},"source_id":"1312.6055","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7986d38a0dcab2c5ae99d6557d683e4d51267744f4d21eeae1a7c32d04b966f","sha256:b23b8957f38d6cd94026945ad6189f60769ba246065ad9df7b13a499a00c8b8a"],"state_sha256":"e9a4054965528f3cc77012fddfe51e24c47123bf93c613a8ff8dae351a1de56b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M1Tgt1ir1U3OhbRvUO47HH7NcJi9QIPqTX3sJv0wN5FyDdg5LaT3JMCRpTQx+7sWg+of/EiiQT3QmMLQsjmaBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T23:38:44.283566Z","bundle_sha256":"e365db7cea29636d0268e2b5f3f7f8bb6934905a0cb2a975e9e227065ec12995"}}