{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:S2YPETY4FSDJE736JVXVBZ7YXO","short_pith_number":"pith:S2YPETY4","canonical_record":{"source":{"id":"1805.11710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-29T21:15:42Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a28f38dcd3fce9d74ab5d63586755b7e2d00513c6e662c5ab69c7660a94dc1aa","abstract_canon_sha256":"9ea5c408d92dc137c13b94094c3ed424eb49e9264ca329ef8d9fc3f3c5293fe1"},"schema_version":"1.0"},"canonical_sha256":"96b0f24f1c2c86927f7e4d6f50e7f8bbaa136a7410b744f5631138b0aa4867c4","source":{"kind":"arxiv","id":"1805.11710","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.11710","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"1805.11710v1","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.11710","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"S2YPETY4FSDJ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"S2YPETY4FSDJE736","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"S2YPETY4","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:S2YPETY4FSDJE736JVXVBZ7YXO","target":"record","payload":{"canonical_record":{"source":{"id":"1805.11710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-29T21:15:42Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a28f38dcd3fce9d74ab5d63586755b7e2d00513c6e662c5ab69c7660a94dc1aa","abstract_canon_sha256":"9ea5c408d92dc137c13b94094c3ed424eb49e9264ca329ef8d9fc3f3c5293fe1"},"schema_version":"1.0"},"canonical_sha256":"96b0f24f1c2c86927f7e4d6f50e7f8bbaa136a7410b744f5631138b0aa4867c4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:36.852569Z","signature_b64":"ZrTflMLDrZzSiM/TebuiNVx8FcBTCKG61XyjdvEdgzglvE+TR1A1uqH452lOaHP5g9LyUunbr036KvS2Q0lEBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"96b0f24f1c2c86927f7e4d6f50e7f8bbaa136a7410b744f5631138b0aa4867c4","last_reissued_at":"2026-05-18T00:14:36.851780Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:36.851780Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.11710","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":"2026-05-18T00:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KievM99lDVFrwJ2gfw2BvCng3R3UXulw1682nydz+TTll2o410mYFxyTVBqGEh/+tlhf+6+hexCVR9BkMJ5tDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T14:22:12.445193Z"},"content_sha256":"d266466aed8af036bb4a9363baa6b4cc7982f3fea3d65da9673c97c8efa31261","schema_version":"1.0","event_id":"sha256:d266466aed8af036bb4a9363baa6b4cc7982f3fea3d65da9673c97c8efa31261"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:S2YPETY4FSDJE736JVXVBZ7YXO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active and Adaptive Sequential learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Jiaxun Lu, Venugopal V. Veeravalli, Yuheng Bu","submitted_at":"2018-05-29T21:15:42Z","abstract_excerpt":"A framework is introduced for actively and adaptively solving a sequence of machine learning problems, which are changing in bounded manner from one time step to the next. An algorithm is developed that actively queries the labels of the most informative samples from an unlabeled data pool, and that adapts to the change by utilizing the information acquired in the previous steps. Our analysis shows that the proposed active learning algorithm based on stochastic gradient descent achieves a near-optimal excess risk performance for maximum likelihood estimation. Furthermore, an estimator of the c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.11710","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":"2026-05-18T00:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g7l7CGGW6Jm+dFgb6OtEnJ8T0PNLDi8VkofoFU3uxwndquvkZ0LIsdZHQKmJMVu7r3axuCgc+USkDopPKppeDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T14:22:12.445566Z"},"content_sha256":"6206c3b697efad6436a0d7a2005fa6b09b680371058870ab5d3a51dd94370a29","schema_version":"1.0","event_id":"sha256:6206c3b697efad6436a0d7a2005fa6b09b680371058870ab5d3a51dd94370a29"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S2YPETY4FSDJE736JVXVBZ7YXO/bundle.json","state_url":"https://pith.science/pith/S2YPETY4FSDJE736JVXVBZ7YXO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S2YPETY4FSDJE736JVXVBZ7YXO/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":"2026-06-04T14:22:12Z","links":{"resolver":"https://pith.science/pith/S2YPETY4FSDJE736JVXVBZ7YXO","bundle":"https://pith.science/pith/S2YPETY4FSDJE736JVXVBZ7YXO/bundle.json","state":"https://pith.science/pith/S2YPETY4FSDJE736JVXVBZ7YXO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S2YPETY4FSDJE736JVXVBZ7YXO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:S2YPETY4FSDJE736JVXVBZ7YXO","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":"9ea5c408d92dc137c13b94094c3ed424eb49e9264ca329ef8d9fc3f3c5293fe1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-29T21:15:42Z","title_canon_sha256":"a28f38dcd3fce9d74ab5d63586755b7e2d00513c6e662c5ab69c7660a94dc1aa"},"schema_version":"1.0","source":{"id":"1805.11710","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.11710","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"1805.11710v1","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.11710","created_at":"2026-05-18T00:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"S2YPETY4FSDJ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"S2YPETY4FSDJE736","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"S2YPETY4","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:6206c3b697efad6436a0d7a2005fa6b09b680371058870ab5d3a51dd94370a29","target":"graph","created_at":"2026-05-18T00:14:36Z","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":"A framework is introduced for actively and adaptively solving a sequence of machine learning problems, which are changing in bounded manner from one time step to the next. An algorithm is developed that actively queries the labels of the most informative samples from an unlabeled data pool, and that adapts to the change by utilizing the information acquired in the previous steps. Our analysis shows that the proposed active learning algorithm based on stochastic gradient descent achieves a near-optimal excess risk performance for maximum likelihood estimation. Furthermore, an estimator of the c","authors_text":"Jiaxun Lu, Venugopal V. Veeravalli, Yuheng Bu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-29T21:15:42Z","title":"Active and Adaptive Sequential learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.11710","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:d266466aed8af036bb4a9363baa6b4cc7982f3fea3d65da9673c97c8efa31261","target":"record","created_at":"2026-05-18T00:14:36Z","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":"9ea5c408d92dc137c13b94094c3ed424eb49e9264ca329ef8d9fc3f3c5293fe1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-29T21:15:42Z","title_canon_sha256":"a28f38dcd3fce9d74ab5d63586755b7e2d00513c6e662c5ab69c7660a94dc1aa"},"schema_version":"1.0","source":{"id":"1805.11710","kind":"arxiv","version":1}},"canonical_sha256":"96b0f24f1c2c86927f7e4d6f50e7f8bbaa136a7410b744f5631138b0aa4867c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"96b0f24f1c2c86927f7e4d6f50e7f8bbaa136a7410b744f5631138b0aa4867c4","first_computed_at":"2026-05-18T00:14:36.851780Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:36.851780Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZrTflMLDrZzSiM/TebuiNVx8FcBTCKG61XyjdvEdgzglvE+TR1A1uqH452lOaHP5g9LyUunbr036KvS2Q0lEBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:36.852569Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.11710","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d266466aed8af036bb4a9363baa6b4cc7982f3fea3d65da9673c97c8efa31261","sha256:6206c3b697efad6436a0d7a2005fa6b09b680371058870ab5d3a51dd94370a29"],"state_sha256":"ba12c886fc68d4f0730d8aab7b6d0678e4ef9fbc45eedab13bfba568cac686e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nyCJw+mfhaq6ME0DrHLBDvOf5AJg0j/462oU7hj2UzG/9wNqYgslCO2xWtUTI/txLkByWCacxT2kDBh/Kd+nCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T14:22:12.447513Z","bundle_sha256":"af397bc8a37a7d6a60c2cb519f23547ff4444a698bd4a4a47ee1a3a8b0766881"}}