{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:DUHXZ5QRFT3XBXDZB7WI2ME2OL","short_pith_number":"pith:DUHXZ5QR","canonical_record":{"source":{"id":"1312.4986","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-17T22:12:52Z","cross_cats_sorted":[],"title_canon_sha256":"c33b7a3c14bbd7d786ec2e2db6063e77f032acb48f2d0446700f520d5722e5bf","abstract_canon_sha256":"822514e052313701b784a8d55afcb79b6f7062c6dddbb9a5353be7ef60455264"},"schema_version":"1.0"},"canonical_sha256":"1d0f7cf6112cf770dc790fec8d309a72f4016921ace7dde2ed6d952f8786884f","source":{"kind":"arxiv","id":"1312.4986","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.4986","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"arxiv_version","alias_value":"1312.4986v1","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.4986","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"pith_short_12","alias_value":"DUHXZ5QRFT3X","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"DUHXZ5QRFT3XBXDZ","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"DUHXZ5QR","created_at":"2026-05-18T12:27:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:DUHXZ5QRFT3XBXDZB7WI2ME2OL","target":"record","payload":{"canonical_record":{"source":{"id":"1312.4986","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-17T22:12:52Z","cross_cats_sorted":[],"title_canon_sha256":"c33b7a3c14bbd7d786ec2e2db6063e77f032acb48f2d0446700f520d5722e5bf","abstract_canon_sha256":"822514e052313701b784a8d55afcb79b6f7062c6dddbb9a5353be7ef60455264"},"schema_version":"1.0"},"canonical_sha256":"1d0f7cf6112cf770dc790fec8d309a72f4016921ace7dde2ed6d952f8786884f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:04:16.643605Z","signature_b64":"fEG98yeqEF2Q6aSn5lTXefVJSIThVAfuPdsmbctOUqEQ6lftVNuO1VAaSH4gc/OLGkpvFBLtdIOoYpegmZTFAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1d0f7cf6112cf770dc790fec8d309a72f4016921ace7dde2ed6d952f8786884f","last_reissued_at":"2026-05-18T03:04:16.642902Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:04:16.642902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1312.4986","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":"2026-05-18T03:04:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jvz3quFKv6khqxnh9mCuzxwRJwIU/eYpT2qd/D30FsA4vHN9gHC8EkARkmUrEKVgursEhUuTaVm1+NJujqEgAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T19:16:40.086850Z"},"content_sha256":"fd2988a0b2ecc443be1e084061e6ba2373c53ccf105b36f57a666f1a789e9b4f","schema_version":"1.0","event_id":"sha256:fd2988a0b2ecc443be1e084061e6ba2373c53ccf105b36f57a666f1a789e9b4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:DUHXZ5QRFT3XBXDZB7WI2ME2OL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Comparative Evaluation of Curriculum Learning with Filtering and Boosting","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Michael R. Smith, Tony Martinez","submitted_at":"2013-12-17T22:12:52Z","abstract_excerpt":"Not all instances in a data set are equally beneficial for inferring a model of the data. Some instances (such as outliers) are detrimental to inferring a model of the data. Several machine learning techniques treat instances in a data set differently during training such as curriculum learning, filtering, and boosting. However, an automated method for determining how beneficial an instance is for inferring a model of the data does not exist. In this paper, we present an automated method that orders the instances in a data set by complexity based on the their likelihood of being misclassified "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.4986","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":"2026-05-18T03:04:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YgaXa77bGGX6Paw/1+F51Ouv4IlUh/XvNyYrFLh7i4BJrO/3L+6fZ//51cQZX5R/Ed3FvR4SgVVbr91mTJLfDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T19:16:40.087184Z"},"content_sha256":"7c6b818f4691993a5d7a9e619a9a9074129bbefbd264e460f505f9d16eadcac3","schema_version":"1.0","event_id":"sha256:7c6b818f4691993a5d7a9e619a9a9074129bbefbd264e460f505f9d16eadcac3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/bundle.json","state_url":"https://pith.science/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/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":"2026-06-20T19:16:40Z","links":{"resolver":"https://pith.science/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL","bundle":"https://pith.science/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/bundle.json","state":"https://pith.science/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DUHXZ5QRFT3XBXDZB7WI2ME2OL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:DUHXZ5QRFT3XBXDZB7WI2ME2OL","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":"822514e052313701b784a8d55afcb79b6f7062c6dddbb9a5353be7ef60455264","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-17T22:12:52Z","title_canon_sha256":"c33b7a3c14bbd7d786ec2e2db6063e77f032acb48f2d0446700f520d5722e5bf"},"schema_version":"1.0","source":{"id":"1312.4986","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.4986","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"arxiv_version","alias_value":"1312.4986v1","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.4986","created_at":"2026-05-18T03:04:16Z"},{"alias_kind":"pith_short_12","alias_value":"DUHXZ5QRFT3X","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"DUHXZ5QRFT3XBXDZ","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"DUHXZ5QR","created_at":"2026-05-18T12:27:43Z"}],"graph_snapshots":[{"event_id":"sha256:7c6b818f4691993a5d7a9e619a9a9074129bbefbd264e460f505f9d16eadcac3","target":"graph","created_at":"2026-05-18T03:04:16Z","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":"Not all instances in a data set are equally beneficial for inferring a model of the data. Some instances (such as outliers) are detrimental to inferring a model of the data. Several machine learning techniques treat instances in a data set differently during training such as curriculum learning, filtering, and boosting. However, an automated method for determining how beneficial an instance is for inferring a model of the data does not exist. In this paper, we present an automated method that orders the instances in a data set by complexity based on the their likelihood of being misclassified ","authors_text":"Michael R. Smith, Tony Martinez","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-17T22:12:52Z","title":"A Comparative Evaluation of Curriculum Learning with Filtering and Boosting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.4986","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:fd2988a0b2ecc443be1e084061e6ba2373c53ccf105b36f57a666f1a789e9b4f","target":"record","created_at":"2026-05-18T03:04:16Z","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":"822514e052313701b784a8d55afcb79b6f7062c6dddbb9a5353be7ef60455264","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-12-17T22:12:52Z","title_canon_sha256":"c33b7a3c14bbd7d786ec2e2db6063e77f032acb48f2d0446700f520d5722e5bf"},"schema_version":"1.0","source":{"id":"1312.4986","kind":"arxiv","version":1}},"canonical_sha256":"1d0f7cf6112cf770dc790fec8d309a72f4016921ace7dde2ed6d952f8786884f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d0f7cf6112cf770dc790fec8d309a72f4016921ace7dde2ed6d952f8786884f","first_computed_at":"2026-05-18T03:04:16.642902Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:04:16.642902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fEG98yeqEF2Q6aSn5lTXefVJSIThVAfuPdsmbctOUqEQ6lftVNuO1VAaSH4gc/OLGkpvFBLtdIOoYpegmZTFAA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:04:16.643605Z","signed_message":"canonical_sha256_bytes"},"source_id":"1312.4986","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fd2988a0b2ecc443be1e084061e6ba2373c53ccf105b36f57a666f1a789e9b4f","sha256:7c6b818f4691993a5d7a9e619a9a9074129bbefbd264e460f505f9d16eadcac3"],"state_sha256":"af075281485517485883a83e0f0f019fdfbdccb8e1159a14a3977f6988cb2ad7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n1deldHJ1IUh55XNZCcigUA0xGA+H40qKLZLTTKshvyar5/KEMSFQUc0DJ6096d+R7c44x982RZGwNXG3ezHBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T19:16:40.089041Z","bundle_sha256":"a414728a4b773aace477f0bb399580f6fa1290f8de8d450276b09309fe74a468"}}