{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:5BHWWPSGXZAZ6VX3QUHTXGVLFE","short_pith_number":"pith:5BHWWPSG","canonical_record":{"source":{"id":"1708.05106","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-16T23:38:35Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"2a8f793f4c232b0d136997b4d6928cc0b5d089e4cf9e6ec66fec5e745baf301f","abstract_canon_sha256":"cee71763ac29a41f3a05238dafb4c1fc3b8e1576428f5de45255d96c95a686f9"},"schema_version":"1.0"},"canonical_sha256":"e84f6b3e46be419f56fb850f3b9aab29222d93367034cd6ad2e963132306a4a9","source":{"kind":"arxiv","id":"1708.05106","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.05106","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"arxiv_version","alias_value":"1708.05106v2","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.05106","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"pith_short_12","alias_value":"5BHWWPSGXZAZ","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5BHWWPSGXZAZ6VX3","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5BHWWPSG","created_at":"2026-05-18T12:31:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:5BHWWPSGXZAZ6VX3QUHTXGVLFE","target":"record","payload":{"canonical_record":{"source":{"id":"1708.05106","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-16T23:38:35Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"2a8f793f4c232b0d136997b4d6928cc0b5d089e4cf9e6ec66fec5e745baf301f","abstract_canon_sha256":"cee71763ac29a41f3a05238dafb4c1fc3b8e1576428f5de45255d96c95a686f9"},"schema_version":"1.0"},"canonical_sha256":"e84f6b3e46be419f56fb850f3b9aab29222d93367034cd6ad2e963132306a4a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:19.305883Z","signature_b64":"xhZBI3cbBFTABk7KlKuBVsyOPLuw/uwkvYdNJmeolTWjSG9wJRLURA6DQ+MUsjuCFA8N0KfexpmpaQqmfg8FDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e84f6b3e46be419f56fb850f3b9aab29222d93367034cd6ad2e963132306a4a9","last_reissued_at":"2026-05-18T00:10:19.305361Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:19.305361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.05106","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:10:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n/se00300tB5v81XmX7n3njPD/Lw0F00Q5AK4evf4OVa9/uBa9yG6Pr6xkspz90j4AyVBE4PbTK7exTzx+O8Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T23:00:38.024206Z"},"content_sha256":"60613b7b978d58fafcbec4549f10d6f9347e66d9a932f5d622e814c1fe9bfd82","schema_version":"1.0","event_id":"sha256:60613b7b978d58fafcbec4549f10d6f9347e66d9a932f5d622e814c1fe9bfd82"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:5BHWWPSGXZAZ6VX3QUHTXGVLFE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Arin Chaudhuri, Carol Sadek, Deovrat Kakde, Laura Gonzalez, Seunghyun Kong","submitted_at":"2017-08-16T23:38:35Z","abstract_excerpt":"Support vector data description (SVDD) is a popular technique for detecting anomalies. The SVDD classifier partitions the whole space into an inlier region, which consists of the region near the training data, and an outlier region, which consists of points away from the training data. The computation of the SVDD classifier requires a kernel function, and the Gaussian kernel is a common choice for the kernel function. The Gaussian kernel has a bandwidth parameter, whose value is important for good results. A small bandwidth leads to overfitting, and the resulting SVDD classifier overestimates "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.05106","kind":"arxiv","version":2},"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":"2026-05-18T00:10:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6fK5sV48AIOx97gJFbgp09QkgGVLkeHOuG4iWH/YwxjAzGYzoHJ3fe+HirGvQR9cCAUvFI66HIb/pQLdZpTDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-20T23:00:38.024580Z"},"content_sha256":"c0a770b4111e88838ed02c86f4a77a93b7debae17c43c179127ad8124879b6fc","schema_version":"1.0","event_id":"sha256:c0a770b4111e88838ed02c86f4a77a93b7debae17c43c179127ad8124879b6fc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/bundle.json","state_url":"https://pith.science/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/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":"2026-06-20T23:00:38Z","links":{"resolver":"https://pith.science/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE","bundle":"https://pith.science/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/bundle.json","state":"https://pith.science/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5BHWWPSGXZAZ6VX3QUHTXGVLFE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5BHWWPSGXZAZ6VX3QUHTXGVLFE","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":"cee71763ac29a41f3a05238dafb4c1fc3b8e1576428f5de45255d96c95a686f9","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-16T23:38:35Z","title_canon_sha256":"2a8f793f4c232b0d136997b4d6928cc0b5d089e4cf9e6ec66fec5e745baf301f"},"schema_version":"1.0","source":{"id":"1708.05106","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.05106","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"arxiv_version","alias_value":"1708.05106v2","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.05106","created_at":"2026-05-18T00:10:19Z"},{"alias_kind":"pith_short_12","alias_value":"5BHWWPSGXZAZ","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5BHWWPSGXZAZ6VX3","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5BHWWPSG","created_at":"2026-05-18T12:31:00Z"}],"graph_snapshots":[{"event_id":"sha256:c0a770b4111e88838ed02c86f4a77a93b7debae17c43c179127ad8124879b6fc","target":"graph","created_at":"2026-05-18T00:10:19Z","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":"Support vector data description (SVDD) is a popular technique for detecting anomalies. The SVDD classifier partitions the whole space into an inlier region, which consists of the region near the training data, and an outlier region, which consists of points away from the training data. The computation of the SVDD classifier requires a kernel function, and the Gaussian kernel is a common choice for the kernel function. The Gaussian kernel has a bandwidth parameter, whose value is important for good results. A small bandwidth leads to overfitting, and the resulting SVDD classifier overestimates ","authors_text":"Arin Chaudhuri, Carol Sadek, Deovrat Kakde, Laura Gonzalez, Seunghyun Kong","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-16T23:38:35Z","title":"The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.05106","kind":"arxiv","version":2},"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":"sha256:60613b7b978d58fafcbec4549f10d6f9347e66d9a932f5d622e814c1fe9bfd82","target":"record","created_at":"2026-05-18T00:10:19Z","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":"cee71763ac29a41f3a05238dafb4c1fc3b8e1576428f5de45255d96c95a686f9","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-16T23:38:35Z","title_canon_sha256":"2a8f793f4c232b0d136997b4d6928cc0b5d089e4cf9e6ec66fec5e745baf301f"},"schema_version":"1.0","source":{"id":"1708.05106","kind":"arxiv","version":2}},"canonical_sha256":"e84f6b3e46be419f56fb850f3b9aab29222d93367034cd6ad2e963132306a4a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e84f6b3e46be419f56fb850f3b9aab29222d93367034cd6ad2e963132306a4a9","first_computed_at":"2026-05-18T00:10:19.305361Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:19.305361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xhZBI3cbBFTABk7KlKuBVsyOPLuw/uwkvYdNJmeolTWjSG9wJRLURA6DQ+MUsjuCFA8N0KfexpmpaQqmfg8FDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:19.305883Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.05106","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60613b7b978d58fafcbec4549f10d6f9347e66d9a932f5d622e814c1fe9bfd82","sha256:c0a770b4111e88838ed02c86f4a77a93b7debae17c43c179127ad8124879b6fc"],"state_sha256":"279fb1947b839004836f4885b1aca4949469f80e2055dbae05456c22ee81955c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mQGRpkeEg1+p90kRtBRiyz2AGirDYEvO5Nybo4VxJAreSirJcWk/Mv/BRv+93BU/3SkqVd0QiMtjrzbxkyMaBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-20T23:00:38.026480Z","bundle_sha256":"2fae8a4ffb10e8464b527290a2095e55c6962979fb1962b422fcd1e01ccd334e"}}