{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:35BV5KTLPP5FWE7ZNNRZ6GKSS6","short_pith_number":"pith:35BV5KTL","canonical_record":{"source":{"id":"1704.07433","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-24T19:48:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d01c13b5057538c6dc5c23645906f249abf822b9e11636df2babbd2f67aaabd9","abstract_canon_sha256":"e20015b82249e8a22ebc078f986077e346b54b104f41bc62ea573e21b292e77a"},"schema_version":"1.0"},"canonical_sha256":"df435eaa6b7bfa5b13f96b639f195297bda3c5e94a0234c4525987ee868cdaf5","source":{"kind":"arxiv","id":"1704.07433","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.07433","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"arxiv_version","alias_value":"1704.07433v4","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.07433","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"pith_short_12","alias_value":"35BV5KTLPP5F","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"35BV5KTLPP5FWE7Z","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"35BV5KTL","created_at":"2026-05-18T12:30:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:35BV5KTLPP5FWE7ZNNRZ6GKSS6","target":"record","payload":{"canonical_record":{"source":{"id":"1704.07433","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-24T19:48:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"d01c13b5057538c6dc5c23645906f249abf822b9e11636df2babbd2f67aaabd9","abstract_canon_sha256":"e20015b82249e8a22ebc078f986077e346b54b104f41bc62ea573e21b292e77a"},"schema_version":"1.0"},"canonical_sha256":"df435eaa6b7bfa5b13f96b639f195297bda3c5e94a0234c4525987ee868cdaf5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:26:37.146140Z","signature_b64":"e5qtAAAt3JWIVShWn7lA/WGl6h1EOXyLVgAxMMhefQq7cv8O91dl+LyuG4DGHfJnopcmH8pYJ4Tsx3uGV3m9BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df435eaa6b7bfa5b13f96b639f195297bda3c5e94a0234c4525987ee868cdaf5","last_reissued_at":"2026-05-18T00:26:37.145475Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:26:37.145475Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.07433","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:26:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IH5CQKiT4ioX9m+wQYXGt1dq1vssehhDCs7dEVvyUpKA7tw1yu1sJ0EcaPUrMJKLkBAC1abbN9D7LyXQz+2oDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:37:40.033441Z"},"content_sha256":"81cdc2a02b44618e3fb6a0607eb350c9a09e9a2aeac69f01bcf560e8662a9930","schema_version":"1.0","event_id":"sha256:81cdc2a02b44618e3fb6a0607eb350c9a09e9a2aeac69f01bcf560e8662a9930"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:35BV5KTLPP5FWE7ZNNRZ6GKSS6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Andrew McCallum, Erik Learned-Miller, Haw-Shiuan Chang","submitted_at":"2017-04-24T19:48:49Z","abstract_excerpt":"Self-paced learning and hard example mining re-weight training instances to improve learning accuracy. This paper presents two improved alternatives based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD): the variance in predicted probability of the correct class across iterations of mini-batch SGD, and the proximity of the correct class probability to the decision threshold. Extensive experimental results on six datasets show that our methods reliably improve accuracy in various network architectures, including additional gains on top of other popular traini"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.07433","kind":"arxiv","version":4},"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":"2026-05-18T00:26:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6yi9/dc0xA+z7C0p2/s456GspdEVjPlM+inzJoO1mj9yYo2ChmK7eoJrQYcggZUi+nrb0RXslgWg9fKPAxD4BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:37:40.033832Z"},"content_sha256":"aa5a954312fd17b6674d118eab19105ba51babe4e9e528fbdcfea731cc631991","schema_version":"1.0","event_id":"sha256:aa5a954312fd17b6674d118eab19105ba51babe4e9e528fbdcfea731cc631991"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/bundle.json","state_url":"https://pith.science/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/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":"2026-05-27T12:37:40Z","links":{"resolver":"https://pith.science/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6","bundle":"https://pith.science/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/bundle.json","state":"https://pith.science/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/35BV5KTLPP5FWE7ZNNRZ6GKSS6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:35BV5KTLPP5FWE7ZNNRZ6GKSS6","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":"e20015b82249e8a22ebc078f986077e346b54b104f41bc62ea573e21b292e77a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-24T19:48:49Z","title_canon_sha256":"d01c13b5057538c6dc5c23645906f249abf822b9e11636df2babbd2f67aaabd9"},"schema_version":"1.0","source":{"id":"1704.07433","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.07433","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"arxiv_version","alias_value":"1704.07433v4","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.07433","created_at":"2026-05-18T00:26:37Z"},{"alias_kind":"pith_short_12","alias_value":"35BV5KTLPP5F","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"35BV5KTLPP5FWE7Z","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"35BV5KTL","created_at":"2026-05-18T12:30:58Z"}],"graph_snapshots":[{"event_id":"sha256:aa5a954312fd17b6674d118eab19105ba51babe4e9e528fbdcfea731cc631991","target":"graph","created_at":"2026-05-18T00:26:37Z","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":"Self-paced learning and hard example mining re-weight training instances to improve learning accuracy. This paper presents two improved alternatives based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD): the variance in predicted probability of the correct class across iterations of mini-batch SGD, and the proximity of the correct class probability to the decision threshold. Extensive experimental results on six datasets show that our methods reliably improve accuracy in various network architectures, including additional gains on top of other popular traini","authors_text":"Andrew McCallum, Erik Learned-Miller, Haw-Shiuan Chang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-24T19:48:49Z","title":"Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.07433","kind":"arxiv","version":4},"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":"sha256:81cdc2a02b44618e3fb6a0607eb350c9a09e9a2aeac69f01bcf560e8662a9930","target":"record","created_at":"2026-05-18T00:26:37Z","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":"e20015b82249e8a22ebc078f986077e346b54b104f41bc62ea573e21b292e77a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-04-24T19:48:49Z","title_canon_sha256":"d01c13b5057538c6dc5c23645906f249abf822b9e11636df2babbd2f67aaabd9"},"schema_version":"1.0","source":{"id":"1704.07433","kind":"arxiv","version":4}},"canonical_sha256":"df435eaa6b7bfa5b13f96b639f195297bda3c5e94a0234c4525987ee868cdaf5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df435eaa6b7bfa5b13f96b639f195297bda3c5e94a0234c4525987ee868cdaf5","first_computed_at":"2026-05-18T00:26:37.145475Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:26:37.145475Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e5qtAAAt3JWIVShWn7lA/WGl6h1EOXyLVgAxMMhefQq7cv8O91dl+LyuG4DGHfJnopcmH8pYJ4Tsx3uGV3m9BA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:26:37.146140Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.07433","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:81cdc2a02b44618e3fb6a0607eb350c9a09e9a2aeac69f01bcf560e8662a9930","sha256:aa5a954312fd17b6674d118eab19105ba51babe4e9e528fbdcfea731cc631991"],"state_sha256":"bc78e41f9043a5523e8d0144c7caac2db1b5b1377fa227e3e5606d2789bec895"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PLW3A4gYCFrLkr6SKME7JMHGmQtwHwQIine1WY8mEYZAlYc61W5q/upNuMS51Bd3RB1GxzHh8HmTtkNmJJ5JBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T12:37:40.036657Z","bundle_sha256":"ca192e5b74843f4b2feee5fd64cae65c9e094f6c97da5e950f0f271d313f1dbb"}}