{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:JQXDB5UH7OZ3QMH7PLJ632BCTT","short_pith_number":"pith:JQXDB5UH","canonical_record":{"source":{"id":"1707.03220","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-07-11T11:16:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"c422333d9b92542b8eda48d391eed255eeb2ac0ccd402b2f681367b330f4febe","abstract_canon_sha256":"06ba8e03565d834afd66329b26954799f6c79cdcc54a25c46ad246e33188b49e"},"schema_version":"1.0"},"canonical_sha256":"4c2e30f687fbb3b830ff7ad3ede8229cd9e9f14e2a9c4d21803cb6a503501653","source":{"kind":"arxiv","id":"1707.03220","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03220","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03220v3","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03220","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"pith_short_12","alias_value":"JQXDB5UH7OZ3","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"JQXDB5UH7OZ3QMH7","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"JQXDB5UH","created_at":"2026-05-18T12:31:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:JQXDB5UH7OZ3QMH7PLJ632BCTT","target":"record","payload":{"canonical_record":{"source":{"id":"1707.03220","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-07-11T11:16:08Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"c422333d9b92542b8eda48d391eed255eeb2ac0ccd402b2f681367b330f4febe","abstract_canon_sha256":"06ba8e03565d834afd66329b26954799f6c79cdcc54a25c46ad246e33188b49e"},"schema_version":"1.0"},"canonical_sha256":"4c2e30f687fbb3b830ff7ad3ede8229cd9e9f14e2a9c4d21803cb6a503501653","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:56.065059Z","signature_b64":"HfJRM0dC4UrOJry7gICcHN0uszAKs7xS3pjop3idqBBmZs5cNLozf1Uwxs1ch0CIdQ43PDIZ18U4bDe9GgNCAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c2e30f687fbb3b830ff7ad3ede8229cd9e9f14e2a9c4d21803cb6a503501653","last_reissued_at":"2026-05-17T23:52:56.064375Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:56.064375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.03220","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":"2026-05-17T23:52:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wpb4ll3KBrWhpTSiwvtmVLxaZP+fFk/g5tRsSdPCAi7nX3huYJ50+bJ7MCInz7vIH3lcAQbMppcYopeWVNjeAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T23:06:58.007899Z"},"content_sha256":"80a9e3fe2eead7cc5b67b0fcba3714893bd80bb9a4b556705a043c4f48183e25","schema_version":"1.0","event_id":"sha256:80a9e3fe2eead7cc5b67b0fcba3714893bd80bb9a4b556705a043c4f48183e25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:JQXDB5UH7OZ3QMH7PLJ632BCTT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reducing training time by efficient localized kernel regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Nicole M\\\"ucke","submitted_at":"2017-07-11T11:16:08Z","abstract_excerpt":"We study generalization properties of kernel regularized least squares regression based on a partitioning approach. We show that optimal rates of convergence are preserved if the number of local sets grows sufficiently slowly with the sample size. Moreover, the partitioning approach can be efficiently combined with local Nystr\\\"om subsampling, improving computational cost twofold."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03220","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":""},"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":"2026-05-17T23:52:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lUz2nVX40fxDYVqlbaV/+ahqOD0HZdRWejvEUIDyXyuvMRUV7lKcrYk1iqfow6VWjp9Q58GacMDzhHuiGP5aCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T23:06:58.008246Z"},"content_sha256":"86b30f32b5a4ff07f927be528b1cb08e6a1650138d4a6593e2c73ded755fbb2c","schema_version":"1.0","event_id":"sha256:86b30f32b5a4ff07f927be528b1cb08e6a1650138d4a6593e2c73ded755fbb2c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/bundle.json","state_url":"https://pith.science/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/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":"2026-06-22T23:06:58Z","links":{"resolver":"https://pith.science/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT","bundle":"https://pith.science/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/bundle.json","state":"https://pith.science/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JQXDB5UH7OZ3QMH7PLJ632BCTT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:JQXDB5UH7OZ3QMH7PLJ632BCTT","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":"06ba8e03565d834afd66329b26954799f6c79cdcc54a25c46ad246e33188b49e","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-07-11T11:16:08Z","title_canon_sha256":"c422333d9b92542b8eda48d391eed255eeb2ac0ccd402b2f681367b330f4febe"},"schema_version":"1.0","source":{"id":"1707.03220","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.03220","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"arxiv_version","alias_value":"1707.03220v3","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03220","created_at":"2026-05-17T23:52:56Z"},{"alias_kind":"pith_short_12","alias_value":"JQXDB5UH7OZ3","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"JQXDB5UH7OZ3QMH7","created_at":"2026-05-18T12:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"JQXDB5UH","created_at":"2026-05-18T12:31:24Z"}],"graph_snapshots":[{"event_id":"sha256:86b30f32b5a4ff07f927be528b1cb08e6a1650138d4a6593e2c73ded755fbb2c","target":"graph","created_at":"2026-05-17T23:52:56Z","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":"We study generalization properties of kernel regularized least squares regression based on a partitioning approach. We show that optimal rates of convergence are preserved if the number of local sets grows sufficiently slowly with the sample size. Moreover, the partitioning approach can be efficiently combined with local Nystr\\\"om subsampling, improving computational cost twofold.","authors_text":"Nicole M\\\"ucke","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-07-11T11:16:08Z","title":"Reducing training time by efficient localized kernel regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03220","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":"sha256:80a9e3fe2eead7cc5b67b0fcba3714893bd80bb9a4b556705a043c4f48183e25","target":"record","created_at":"2026-05-17T23:52:56Z","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":"06ba8e03565d834afd66329b26954799f6c79cdcc54a25c46ad246e33188b49e","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-07-11T11:16:08Z","title_canon_sha256":"c422333d9b92542b8eda48d391eed255eeb2ac0ccd402b2f681367b330f4febe"},"schema_version":"1.0","source":{"id":"1707.03220","kind":"arxiv","version":3}},"canonical_sha256":"4c2e30f687fbb3b830ff7ad3ede8229cd9e9f14e2a9c4d21803cb6a503501653","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c2e30f687fbb3b830ff7ad3ede8229cd9e9f14e2a9c4d21803cb6a503501653","first_computed_at":"2026-05-17T23:52:56.064375Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:56.064375Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HfJRM0dC4UrOJry7gICcHN0uszAKs7xS3pjop3idqBBmZs5cNLozf1Uwxs1ch0CIdQ43PDIZ18U4bDe9GgNCAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:56.065059Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.03220","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80a9e3fe2eead7cc5b67b0fcba3714893bd80bb9a4b556705a043c4f48183e25","sha256:86b30f32b5a4ff07f927be528b1cb08e6a1650138d4a6593e2c73ded755fbb2c"],"state_sha256":"c2da551fa91cd6b60f51328080f5dc8bd93fde26a981d7fc003053ca7344515f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ry0VFucvxspA+N5PmWo0pU3pOi8m6Jkde1NUBR2jwpIllgvSrsW+pRMnRjPA2IIevoueE1H4mothLX4O5UNxAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T23:06:58.010085Z","bundle_sha256":"2610387b47c33e1c8d0f3540c2f92e04921fb26ad3181a2fa37f88317d5820b4"}}