{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:ECPJHOAQOBJYGBDAMSNIQ6UQDR","short_pith_number":"pith:ECPJHOAQ","canonical_record":{"source":{"id":"1310.8004","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T02:11:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b371f4c5c46f1c472b1b01d8c5d48448f0785d11b98edbe6403295eea86ddc0c","abstract_canon_sha256":"fb6df46be95a4b7f99061a4e7fee59540ccbfb46fa0052b38bb32526690689e1"},"schema_version":"1.0"},"canonical_sha256":"209e93b8107053830460649a887a901c412bc2a2e665e53ec0527938da6a5ecc","source":{"kind":"arxiv","id":"1310.8004","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.8004","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"arxiv_version","alias_value":"1310.8004v1","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.8004","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"pith_short_12","alias_value":"ECPJHOAQOBJY","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"ECPJHOAQOBJYGBDA","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"ECPJHOAQ","created_at":"2026-05-18T12:27:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:ECPJHOAQOBJYGBDAMSNIQ6UQDR","target":"record","payload":{"canonical_record":{"source":{"id":"1310.8004","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T02:11:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b371f4c5c46f1c472b1b01d8c5d48448f0785d11b98edbe6403295eea86ddc0c","abstract_canon_sha256":"fb6df46be95a4b7f99061a4e7fee59540ccbfb46fa0052b38bb32526690689e1"},"schema_version":"1.0"},"canonical_sha256":"209e93b8107053830460649a887a901c412bc2a2e665e53ec0527938da6a5ecc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:08:26.305063Z","signature_b64":"+ddAAxRB39o2m3cjo2cIb7uK6v9MI/ifDMcVX6gmSk1J9UGRVnPx11tU6ylA52Rq0gCCh6K+RfN+YJwrgFipCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"209e93b8107053830460649a887a901c412bc2a2e665e53ec0527938da6a5ecc","last_reissued_at":"2026-05-18T03:08:26.304384Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:08:26.304384Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1310.8004","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":"2026-05-18T03:08:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5pKDOTEWPPe9+xegLskHsfq2nKj2/AKpewV5KpWYPyS/92PU96PZySYUhg4+oUXE5zSL/UvQiLzSki5SDQ7pCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T13:17:41.221701Z"},"content_sha256":"8117ccc30e6f7ad09cef20c61502bb8baa8a410da5de9782ea4aa20dba120438","schema_version":"1.0","event_id":"sha256:8117ccc30e6f7ad09cef20c61502bb8baa8a410da5de9782ea4aa20dba120438"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:ECPJHOAQOBJYGBDAMSNIQ6UQDR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Ensemble Learning for Imbalanced Data Streams","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Boyu Wang, Joelle Pineau","submitted_at":"2013-10-30T02:11:48Z","abstract_excerpt":"While both cost-sensitive learning and online learning have been studied extensively, the effort in simultaneously dealing with these two issues is limited. Aiming at this challenge task, a novel learning framework is proposed in this paper. The key idea is based on the fusion of online ensemble algorithms and the state of the art batch mode cost-sensitive bagging/boosting algorithms. Within this framework, two separately developed research areas are bridged together, and a batch of theoretically sound online cost-sensitive bagging and online cost-sensitive boosting algorithms are first propos"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.8004","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":"2026-05-18T03:08:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sxhxbAeAbaPs/PJF5MXBgIb+xjyvorH3CeJKRrpZsh2nSehTPGe/N4NPak8mpZ46m1yycy1VOPBDwcspYN1BCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T13:17:41.222374Z"},"content_sha256":"75a51c3c7b1e523d7f27829ae3559c0947f3cd8d31def598641eba57bf5cc0c2","schema_version":"1.0","event_id":"sha256:75a51c3c7b1e523d7f27829ae3559c0947f3cd8d31def598641eba57bf5cc0c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/bundle.json","state_url":"https://pith.science/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/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":"2026-06-08T13:17:41Z","links":{"resolver":"https://pith.science/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR","bundle":"https://pith.science/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/bundle.json","state":"https://pith.science/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ECPJHOAQOBJYGBDAMSNIQ6UQDR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:ECPJHOAQOBJYGBDAMSNIQ6UQDR","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":"fb6df46be95a4b7f99061a4e7fee59540ccbfb46fa0052b38bb32526690689e1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T02:11:48Z","title_canon_sha256":"b371f4c5c46f1c472b1b01d8c5d48448f0785d11b98edbe6403295eea86ddc0c"},"schema_version":"1.0","source":{"id":"1310.8004","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.8004","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"arxiv_version","alias_value":"1310.8004v1","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.8004","created_at":"2026-05-18T03:08:26Z"},{"alias_kind":"pith_short_12","alias_value":"ECPJHOAQOBJY","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_16","alias_value":"ECPJHOAQOBJYGBDA","created_at":"2026-05-18T12:27:43Z"},{"alias_kind":"pith_short_8","alias_value":"ECPJHOAQ","created_at":"2026-05-18T12:27:43Z"}],"graph_snapshots":[{"event_id":"sha256:75a51c3c7b1e523d7f27829ae3559c0947f3cd8d31def598641eba57bf5cc0c2","target":"graph","created_at":"2026-05-18T03:08:26Z","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":"While both cost-sensitive learning and online learning have been studied extensively, the effort in simultaneously dealing with these two issues is limited. Aiming at this challenge task, a novel learning framework is proposed in this paper. The key idea is based on the fusion of online ensemble algorithms and the state of the art batch mode cost-sensitive bagging/boosting algorithms. Within this framework, two separately developed research areas are bridged together, and a batch of theoretically sound online cost-sensitive bagging and online cost-sensitive boosting algorithms are first propos","authors_text":"Boyu Wang, Joelle Pineau","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T02:11:48Z","title":"Online Ensemble Learning for Imbalanced Data Streams"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.8004","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":"sha256:8117ccc30e6f7ad09cef20c61502bb8baa8a410da5de9782ea4aa20dba120438","target":"record","created_at":"2026-05-18T03:08:26Z","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":"fb6df46be95a4b7f99061a4e7fee59540ccbfb46fa0052b38bb32526690689e1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-10-30T02:11:48Z","title_canon_sha256":"b371f4c5c46f1c472b1b01d8c5d48448f0785d11b98edbe6403295eea86ddc0c"},"schema_version":"1.0","source":{"id":"1310.8004","kind":"arxiv","version":1}},"canonical_sha256":"209e93b8107053830460649a887a901c412bc2a2e665e53ec0527938da6a5ecc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"209e93b8107053830460649a887a901c412bc2a2e665e53ec0527938da6a5ecc","first_computed_at":"2026-05-18T03:08:26.304384Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:08:26.304384Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+ddAAxRB39o2m3cjo2cIb7uK6v9MI/ifDMcVX6gmSk1J9UGRVnPx11tU6ylA52Rq0gCCh6K+RfN+YJwrgFipCg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:08:26.305063Z","signed_message":"canonical_sha256_bytes"},"source_id":"1310.8004","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8117ccc30e6f7ad09cef20c61502bb8baa8a410da5de9782ea4aa20dba120438","sha256:75a51c3c7b1e523d7f27829ae3559c0947f3cd8d31def598641eba57bf5cc0c2"],"state_sha256":"8c66409ee37fc9413c961670a559204a7ed5ae29f76ec52837018de731ac2f77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"63s3wLABQklvvv5+bWXdKhopfrH88EFM+k7E4Zf4YL6x4z9bb55az+FhSiFHZiwU7DsNJ8j9Js1vS4y/3lamDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T13:17:41.225587Z","bundle_sha256":"1bedc96f6929a7177b3c7baa836e6c0b037abc13ed459da7023cbd8b62a41d4c"}}