{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:LHBOXDEKHFR6RNNMGZDTMJBMYI","short_pith_number":"pith:LHBOXDEK","canonical_record":{"source":{"id":"1310.8243","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T17:49:11Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e41bc1bf51ed02aecedbc468f7c712c8d637fa7c14012ba05b73e8787df3091f","abstract_canon_sha256":"26b6936bd112acace01b848f9b2aadbe3f18f4a3dcf156ed707f95df644aefd2"},"schema_version":"1.0"},"canonical_sha256":"59c2eb8c8a3963e8b5ac364736242cc215911c8128e568bc0b769ef725e5810b","source":{"kind":"arxiv","id":"1310.8243","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.8243","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"1310.8243v1","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.8243","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"LHBOXDEKHFR6","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LHBOXDEKHFR6RNNM","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LHBOXDEK","created_at":"2026-05-18T12:27:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:LHBOXDEKHFR6RNNMGZDTMJBMYI","target":"record","payload":{"canonical_record":{"source":{"id":"1310.8243","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T17:49:11Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e41bc1bf51ed02aecedbc468f7c712c8d637fa7c14012ba05b73e8787df3091f","abstract_canon_sha256":"26b6936bd112acace01b848f9b2aadbe3f18f4a3dcf156ed707f95df644aefd2"},"schema_version":"1.0"},"canonical_sha256":"59c2eb8c8a3963e8b5ac364736242cc215911c8128e568bc0b769ef725e5810b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:08:25.644232Z","signature_b64":"D3/X595PseVdlCJpTVLj2fdaujqu1BCLfgjQ7iT3lutLkYIR9i17wQseKf48CCH4ja4F7K7XKDq9tqHPdNWpDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59c2eb8c8a3963e8b5ac364736242cc215911c8128e568bc0b769ef725e5810b","last_reissued_at":"2026-05-18T03:08:25.643584Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:08:25.643584Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1310.8243","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":"2026-05-18T03:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1ip8ZRSc6/LaDpC+mwKLpMbFzoap4TtjfgIHzFSjVovr/vFdbzJYX2dzBL3bE49J7jUEtW0SCwdfbm+sjpYnBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:55:32.259007Z"},"content_sha256":"1f3f7158efefcf94f6e92b86b05b48025f63c97320ae464fbf0161b48275d9e5","schema_version":"1.0","event_id":"sha256:1f3f7158efefcf94f6e92b86b05b48025f63c97320ae464fbf0161b48275d9e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:LHBOXDEKHFR6RNNMGZDTMJBMYI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Para-active learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alekh Agarwal, John Langford, Leon Bottou, Miroslav Dudik","submitted_at":"2013-10-30T17:49:11Z","abstract_excerpt":"Training examples are not all equally informative. Active learning strategies leverage this observation in order to massively reduce the number of examples that need to be labeled. We leverage the same observation to build a generic strategy for parallelizing learning algorithms. This strategy is effective because the search for informative examples is highly parallelizable and because we show that its performance does not deteriorate when the sifting process relies on a slightly outdated model. Parallel active learning is particularly attractive to train nonlinear models with non-linear repre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.8243","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":"2026-05-18T03:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rJ6+KhyNB5oMtEyXM76yhzk9/dKR2CrMKlTCHnBzXTydm+truBKkXX+jLDGhASSIH44FlcyRf7SuFNOXVjMPBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:55:32.259629Z"},"content_sha256":"3cfb8dd5219b0e4028f21470e60037ca1e222cdb2b12c6f93446f54e34df8a82","schema_version":"1.0","event_id":"sha256:3cfb8dd5219b0e4028f21470e60037ca1e222cdb2b12c6f93446f54e34df8a82"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/bundle.json","state_url":"https://pith.science/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/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":"2026-05-27T00:55:32Z","links":{"resolver":"https://pith.science/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI","bundle":"https://pith.science/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/bundle.json","state":"https://pith.science/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LHBOXDEKHFR6RNNMGZDTMJBMYI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:LHBOXDEKHFR6RNNMGZDTMJBMYI","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":"26b6936bd112acace01b848f9b2aadbe3f18f4a3dcf156ed707f95df644aefd2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T17:49:11Z","title_canon_sha256":"e41bc1bf51ed02aecedbc468f7c712c8d637fa7c14012ba05b73e8787df3091f"},"schema_version":"1.0","source":{"id":"1310.8243","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.8243","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"1310.8243v1","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.8243","created_at":"2026-05-18T03:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"LHBOXDEKHFR6","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LHBOXDEKHFR6RNNM","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LHBOXDEK","created_at":"2026-05-18T12:27:51Z"}],"graph_snapshots":[{"event_id":"sha256:3cfb8dd5219b0e4028f21470e60037ca1e222cdb2b12c6f93446f54e34df8a82","target":"graph","created_at":"2026-05-18T03:08:25Z","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":"Training examples are not all equally informative. Active learning strategies leverage this observation in order to massively reduce the number of examples that need to be labeled. We leverage the same observation to build a generic strategy for parallelizing learning algorithms. This strategy is effective because the search for informative examples is highly parallelizable and because we show that its performance does not deteriorate when the sifting process relies on a slightly outdated model. Parallel active learning is particularly attractive to train nonlinear models with non-linear repre","authors_text":"Alekh Agarwal, John Langford, Leon Bottou, Miroslav Dudik","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T17:49:11Z","title":"Para-active learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.8243","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":"sha256:1f3f7158efefcf94f6e92b86b05b48025f63c97320ae464fbf0161b48275d9e5","target":"record","created_at":"2026-05-18T03:08:25Z","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":"26b6936bd112acace01b848f9b2aadbe3f18f4a3dcf156ed707f95df644aefd2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T17:49:11Z","title_canon_sha256":"e41bc1bf51ed02aecedbc468f7c712c8d637fa7c14012ba05b73e8787df3091f"},"schema_version":"1.0","source":{"id":"1310.8243","kind":"arxiv","version":1}},"canonical_sha256":"59c2eb8c8a3963e8b5ac364736242cc215911c8128e568bc0b769ef725e5810b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59c2eb8c8a3963e8b5ac364736242cc215911c8128e568bc0b769ef725e5810b","first_computed_at":"2026-05-18T03:08:25.643584Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:08:25.643584Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D3/X595PseVdlCJpTVLj2fdaujqu1BCLfgjQ7iT3lutLkYIR9i17wQseKf48CCH4ja4F7K7XKDq9tqHPdNWpDg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:08:25.644232Z","signed_message":"canonical_sha256_bytes"},"source_id":"1310.8243","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1f3f7158efefcf94f6e92b86b05b48025f63c97320ae464fbf0161b48275d9e5","sha256:3cfb8dd5219b0e4028f21470e60037ca1e222cdb2b12c6f93446f54e34df8a82"],"state_sha256":"61cb0c2601cc8d3af667881b096607724d177b6ca91a66d84c3cf3968313c036"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IAbzFPDXbWHfKdqWnfqrKZGzoQKCtvAaYD3BoWxrMLpdDpDb43rGrvPZ4TUYWWFVDAG6G49dWl1DgZY8w1iOCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T00:55:32.262507Z","bundle_sha256":"c0d1e9f7ab19415616a9366a7b31b9d3aab98e2d0718ec09bf2253b14c3785db"}}