{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DYOXBZ3B3XR4TCTC32SJQUSE32","short_pith_number":"pith:DYOXBZ3B","canonical_record":{"source":{"id":"2602.22101","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-25T16:48:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"61a465639497570fbd4d9c90fd15c6d9a60b4d9b46b8bdbbb9adc3dbc4de9f72","abstract_canon_sha256":"e52bdfe47c17add486b7046c57aa7bc352e5c899539333db1e456a4a0680f7e3"},"schema_version":"1.0"},"canonical_sha256":"1e1d70e761dde3c98a62dea4985244de9646a98b2a6ccaa9b4f5f54bd34b3ed0","source":{"kind":"arxiv","id":"2602.22101","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.22101","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"arxiv_version","alias_value":"2602.22101v3","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.22101","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_12","alias_value":"DYOXBZ3B3XR4","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_16","alias_value":"DYOXBZ3B3XR4TCTC","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_8","alias_value":"DYOXBZ3B","created_at":"2026-06-02T02:04:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DYOXBZ3B3XR4TCTC32SJQUSE32","target":"record","payload":{"canonical_record":{"source":{"id":"2602.22101","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-25T16:48:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"61a465639497570fbd4d9c90fd15c6d9a60b4d9b46b8bdbbb9adc3dbc4de9f72","abstract_canon_sha256":"e52bdfe47c17add486b7046c57aa7bc352e5c899539333db1e456a4a0680f7e3"},"schema_version":"1.0"},"canonical_sha256":"1e1d70e761dde3c98a62dea4985244de9646a98b2a6ccaa9b4f5f54bd34b3ed0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T02:04:15.228994Z","signature_b64":"uCh2GxSDYMSiUx3svS0yxUxoBOpMRbUGbisTwN7cxXLZ0+OLNNRks1n2SwSlzsZWWZYZgSo3Z9ltYJoleRilCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e1d70e761dde3c98a62dea4985244de9646a98b2a6ccaa9b4f5f54bd34b3ed0","last_reissued_at":"2026-06-02T02:04:15.228491Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T02:04:15.228491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.22101","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-02T02:04:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5rgGSlqbKKXnaBCiI3ihsdgzwDFFCWDad6jLkdNqy3KvjsdPYsHyUUphPVRaYCoqhNBjc3WWtBYLl6Sh+3VTAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T15:42:27.756471Z"},"content_sha256":"798a7e3e0eda708de863e2da0e2e8d1b7e62885da5af0e6fe96776ee9d81633f","schema_version":"1.0","event_id":"sha256:798a7e3e0eda708de863e2da0e2e8d1b7e62885da5af0e6fe96776ee9d81633f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DYOXBZ3B3XR4TCTC32SJQUSE32","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Imbalanced Regression with Hoeffding Trees","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dimitrios I. Diochnos, Pantia-Marina Alchirch","submitted_at":"2026-02-25T16:48:07Z","abstract_excerpt":"Many real-world applications generate continuous data streams for regression. Hoeffding trees and their variants have a long-standing tradition due to their effectiveness, either alone or as base models in broader ensembles. Recent batch-learning work shows that kernel density estimation (KDE) improves smoothed predictions in imbalanced regression [Yang et al., 2021], while hierarchical shrinkage (HS) provides post-hoc regularization for decision trees without modifying their structure [Agarwal et al., 2022]. We extend KDE to streaming settings via a telescoping formulation and integrate HS in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.22101","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2602.22101/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-06-02T02:04:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xpABvHo88Tk85fBazyhrMuszeGOcA7tw/m0A1yFANTdtlw08MFNNMSIiQ+duPEQ/+c21LYSoY/cks9aKLJBKDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-21T15:42:27.756900Z"},"content_sha256":"b2320641d5d52f00bc17f62e04d29c32264c07c994f72255bf0641309c42b8ff","schema_version":"1.0","event_id":"sha256:b2320641d5d52f00bc17f62e04d29c32264c07c994f72255bf0641309c42b8ff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/bundle.json","state_url":"https://pith.science/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/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":"2026-06-21T15:42:27Z","links":{"resolver":"https://pith.science/pith/DYOXBZ3B3XR4TCTC32SJQUSE32","bundle":"https://pith.science/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/bundle.json","state":"https://pith.science/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DYOXBZ3B3XR4TCTC32SJQUSE32/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DYOXBZ3B3XR4TCTC32SJQUSE32","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":"e52bdfe47c17add486b7046c57aa7bc352e5c899539333db1e456a4a0680f7e3","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-25T16:48:07Z","title_canon_sha256":"61a465639497570fbd4d9c90fd15c6d9a60b4d9b46b8bdbbb9adc3dbc4de9f72"},"schema_version":"1.0","source":{"id":"2602.22101","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.22101","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"arxiv_version","alias_value":"2602.22101v3","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.22101","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_12","alias_value":"DYOXBZ3B3XR4","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_16","alias_value":"DYOXBZ3B3XR4TCTC","created_at":"2026-06-02T02:04:15Z"},{"alias_kind":"pith_short_8","alias_value":"DYOXBZ3B","created_at":"2026-06-02T02:04:15Z"}],"graph_snapshots":[{"event_id":"sha256:b2320641d5d52f00bc17f62e04d29c32264c07c994f72255bf0641309c42b8ff","target":"graph","created_at":"2026-06-02T02:04:15Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2602.22101/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Many real-world applications generate continuous data streams for regression. Hoeffding trees and their variants have a long-standing tradition due to their effectiveness, either alone or as base models in broader ensembles. Recent batch-learning work shows that kernel density estimation (KDE) improves smoothed predictions in imbalanced regression [Yang et al., 2021], while hierarchical shrinkage (HS) provides post-hoc regularization for decision trees without modifying their structure [Agarwal et al., 2022]. We extend KDE to streaming settings via a telescoping formulation and integrate HS in","authors_text":"Dimitrios I. Diochnos, Pantia-Marina Alchirch","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-25T16:48:07Z","title":"On Imbalanced Regression with Hoeffding Trees"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.22101","kind":"arxiv","version":3},"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":"sha256:798a7e3e0eda708de863e2da0e2e8d1b7e62885da5af0e6fe96776ee9d81633f","target":"record","created_at":"2026-06-02T02:04:15Z","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":"e52bdfe47c17add486b7046c57aa7bc352e5c899539333db1e456a4a0680f7e3","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-25T16:48:07Z","title_canon_sha256":"61a465639497570fbd4d9c90fd15c6d9a60b4d9b46b8bdbbb9adc3dbc4de9f72"},"schema_version":"1.0","source":{"id":"2602.22101","kind":"arxiv","version":3}},"canonical_sha256":"1e1d70e761dde3c98a62dea4985244de9646a98b2a6ccaa9b4f5f54bd34b3ed0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e1d70e761dde3c98a62dea4985244de9646a98b2a6ccaa9b4f5f54bd34b3ed0","first_computed_at":"2026-06-02T02:04:15.228491Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T02:04:15.228491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uCh2GxSDYMSiUx3svS0yxUxoBOpMRbUGbisTwN7cxXLZ0+OLNNRks1n2SwSlzsZWWZYZgSo3Z9ltYJoleRilCQ==","signature_status":"signed_v1","signed_at":"2026-06-02T02:04:15.228994Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.22101","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:798a7e3e0eda708de863e2da0e2e8d1b7e62885da5af0e6fe96776ee9d81633f","sha256:b2320641d5d52f00bc17f62e04d29c32264c07c994f72255bf0641309c42b8ff"],"state_sha256":"48b7eea5baae9ec70470b8910c404ead044d6521708e3315df5c25c27756cde3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jd99TElUMmS7pisju2ttYQc0SBlGGydJk2zoEuGrBH2eq3hi2wgvTudD/B+C0GmPlYFIizmd/XkLOqykPGyWDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-21T15:42:27.758974Z","bundle_sha256":"39943713055920ddfe0309615cc64e9c219f25a898b5babf5bfe3b1457777411"}}