{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:L6KXYS3JBOQFRIJ6QAOJRCORML","short_pith_number":"pith:L6KXYS3J","canonical_record":{"source":{"id":"1608.01410","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-08-04T01:33:34Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"fceff052236830a1ff74893ad24d7c4b76bf44210d57f3684581cc53b5bc6436","abstract_canon_sha256":"7ea6b0e9db8e9c4a19784e8d4e60ad1163233f25f6034106890b195bc8f1d940"},"schema_version":"1.0"},"canonical_sha256":"5f957c4b690ba058a13e801c9889d162f215fc3afbec541357ea6e3d3aea0775","source":{"kind":"arxiv","id":"1608.01410","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.01410","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"1608.01410v1","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.01410","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"L6KXYS3JBOQF","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"L6KXYS3JBOQFRIJ6","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"L6KXYS3J","created_at":"2026-05-18T12:30:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:L6KXYS3JBOQFRIJ6QAOJRCORML","target":"record","payload":{"canonical_record":{"source":{"id":"1608.01410","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-08-04T01:33:34Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"fceff052236830a1ff74893ad24d7c4b76bf44210d57f3684581cc53b5bc6436","abstract_canon_sha256":"7ea6b0e9db8e9c4a19784e8d4e60ad1163233f25f6034106890b195bc8f1d940"},"schema_version":"1.0"},"canonical_sha256":"5f957c4b690ba058a13e801c9889d162f215fc3afbec541357ea6e3d3aea0775","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:09:52.522688Z","signature_b64":"3+O0cwfpsDb4YnWuxQ913ytiyq/CFy7EUqvxz5GImVXAcM+gERZ9qU34U0VXXS3btBnMrJMDkm1az6jJnqE+Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f957c4b690ba058a13e801c9889d162f215fc3afbec541357ea6e3d3aea0775","last_reissued_at":"2026-05-18T01:09:52.522112Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:09:52.522112Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1608.01410","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":"2026-05-18T01:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gHfSSNwKmXw/g+hG9B2H+bvCXSWCwPo3NNNkf3hE0G5ZBTufHq+GKouExtuHN1xsE33TFHYNoHRda6dZB30iBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T16:20:24.347449Z"},"content_sha256":"5539236a667626742b2876e75e7a4f5cdcb79a7325a53fe88d6bd9ca244c2fb4","schema_version":"1.0","event_id":"sha256:5539236a667626742b2876e75e7a4f5cdcb79a7325a53fe88d6bd9ca244c2fb4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:L6KXYS3JBOQFRIJ6QAOJRCORML","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian Kernel and Mutual $k$-Nearest Neighbor Regression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Hyun-Chul Kim","submitted_at":"2016-08-04T01:33:34Z","abstract_excerpt":"We propose Bayesian extensions of two nonparametric regression methods which are kernel and mutual $k$-nearest neighbor regression methods. Derived based on Gaussian process models for regression, the extensions provide distributions for target value estimates and the framework to select the hyperparameters. It is shown that both the proposed methods asymptotically converge to kernel and mutual $k$-nearest neighbor regression methods, respectively. The simulation results show that the proposed methods can select proper hyperparameters and are better than or comparable to the former methods for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.01410","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":"2026-05-18T01:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6Oe22iZuurmhYCnMggAjKgZqSmDAYNS3hN7h+JD/V/b8afIB3oN+ysn2teHXRNXQP2WnslPJhrXM36YhOHd6Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T16:20:24.347790Z"},"content_sha256":"e40004f15d036ae094ac96690213917ef5f07b3d00f12b3ee99aa354da6c69a2","schema_version":"1.0","event_id":"sha256:e40004f15d036ae094ac96690213917ef5f07b3d00f12b3ee99aa354da6c69a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/bundle.json","state_url":"https://pith.science/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/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":"2026-06-05T16:20:24Z","links":{"resolver":"https://pith.science/pith/L6KXYS3JBOQFRIJ6QAOJRCORML","bundle":"https://pith.science/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/bundle.json","state":"https://pith.science/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L6KXYS3JBOQFRIJ6QAOJRCORML/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:L6KXYS3JBOQFRIJ6QAOJRCORML","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":"7ea6b0e9db8e9c4a19784e8d4e60ad1163233f25f6034106890b195bc8f1d940","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-08-04T01:33:34Z","title_canon_sha256":"fceff052236830a1ff74893ad24d7c4b76bf44210d57f3684581cc53b5bc6436"},"schema_version":"1.0","source":{"id":"1608.01410","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.01410","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"1608.01410v1","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.01410","created_at":"2026-05-18T01:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"L6KXYS3JBOQF","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"L6KXYS3JBOQFRIJ6","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"L6KXYS3J","created_at":"2026-05-18T12:30:29Z"}],"graph_snapshots":[{"event_id":"sha256:e40004f15d036ae094ac96690213917ef5f07b3d00f12b3ee99aa354da6c69a2","target":"graph","created_at":"2026-05-18T01:09:52Z","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 propose Bayesian extensions of two nonparametric regression methods which are kernel and mutual $k$-nearest neighbor regression methods. Derived based on Gaussian process models for regression, the extensions provide distributions for target value estimates and the framework to select the hyperparameters. It is shown that both the proposed methods asymptotically converge to kernel and mutual $k$-nearest neighbor regression methods, respectively. The simulation results show that the proposed methods can select proper hyperparameters and are better than or comparable to the former methods for","authors_text":"Hyun-Chul Kim","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-08-04T01:33:34Z","title":"Bayesian Kernel and Mutual $k$-Nearest Neighbor Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.01410","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":"sha256:5539236a667626742b2876e75e7a4f5cdcb79a7325a53fe88d6bd9ca244c2fb4","target":"record","created_at":"2026-05-18T01:09:52Z","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":"7ea6b0e9db8e9c4a19784e8d4e60ad1163233f25f6034106890b195bc8f1d940","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-08-04T01:33:34Z","title_canon_sha256":"fceff052236830a1ff74893ad24d7c4b76bf44210d57f3684581cc53b5bc6436"},"schema_version":"1.0","source":{"id":"1608.01410","kind":"arxiv","version":1}},"canonical_sha256":"5f957c4b690ba058a13e801c9889d162f215fc3afbec541357ea6e3d3aea0775","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f957c4b690ba058a13e801c9889d162f215fc3afbec541357ea6e3d3aea0775","first_computed_at":"2026-05-18T01:09:52.522112Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:09:52.522112Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3+O0cwfpsDb4YnWuxQ913ytiyq/CFy7EUqvxz5GImVXAcM+gERZ9qU34U0VXXS3btBnMrJMDkm1az6jJnqE+Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:09:52.522688Z","signed_message":"canonical_sha256_bytes"},"source_id":"1608.01410","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5539236a667626742b2876e75e7a4f5cdcb79a7325a53fe88d6bd9ca244c2fb4","sha256:e40004f15d036ae094ac96690213917ef5f07b3d00f12b3ee99aa354da6c69a2"],"state_sha256":"b9438280d290cfc196605319b3ed7bc4f61bae443833b676cc769435db720c29"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cc9Irq7EIfN0aszjoo8JD2UvbkVCN69oo7LgCnZZnzNcoZlb+GVdV4g7zu2NmGY+J06K4NZhXIK2BcOfR2TeBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T16:20:24.349708Z","bundle_sha256":"de74f39a791768bcbdd590dae41f9ec6b0dc12b6c0e23af5054767faef7fa762"}}