{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:MZZZNCLA7DAOQ2QXRXLT3EJX24","short_pith_number":"pith:MZZZNCLA","canonical_record":{"source":{"id":"1210.4347","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-10-16T10:26:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6be83edbe490250e304ddbdacd1f6925f6675dfc2a1f7a83ad71abbba8a74e48","abstract_canon_sha256":"c9eeead29734594d3e8b3dd13ef7fd2163f82b44cd712cef22954edf991d60e9"},"schema_version":"1.0"},"canonical_sha256":"6673968960f8c0e86a178dd73d9137d7269949758d2f50ce8e5770d251ead39a","source":{"kind":"arxiv","id":"1210.4347","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1210.4347","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"arxiv_version","alias_value":"1210.4347v1","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.4347","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"pith_short_12","alias_value":"MZZZNCLA7DAO","created_at":"2026-05-18T12:27:16Z"},{"alias_kind":"pith_short_16","alias_value":"MZZZNCLA7DAOQ2QX","created_at":"2026-05-18T12:27:16Z"},{"alias_kind":"pith_short_8","alias_value":"MZZZNCLA","created_at":"2026-05-18T12:27:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:MZZZNCLA7DAOQ2QXRXLT3EJX24","target":"record","payload":{"canonical_record":{"source":{"id":"1210.4347","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-10-16T10:26:29Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6be83edbe490250e304ddbdacd1f6925f6675dfc2a1f7a83ad71abbba8a74e48","abstract_canon_sha256":"c9eeead29734594d3e8b3dd13ef7fd2163f82b44cd712cef22954edf991d60e9"},"schema_version":"1.0"},"canonical_sha256":"6673968960f8c0e86a178dd73d9137d7269949758d2f50ce8e5770d251ead39a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:43:06.259845Z","signature_b64":"pUqfFm1ThiFqJ3d/muHgMozyNSffKnaD6NDEqtBPW5AlIt0urLQsEmBhCnoYjIc45u3/0IXydmfptJDwVwZBBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6673968960f8c0e86a178dd73d9137d7269949758d2f50ce8e5770d251ead39a","last_reissued_at":"2026-05-18T03:43:06.259144Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:43:06.259144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1210.4347","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":"2026-05-18T03:43:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ON6/q3ZUwtpOU5jr5habMFpy8pNb/boeiLxvoHS4LRin4tFUkhBcuCqTE0VtAYE+UpoT/U9chC3hO5+pRCphDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:58:02.543356Z"},"content_sha256":"e253aa917b0b5ee44e519224e135dbf211028d788ed170009678d2290c3fc144","schema_version":"1.0","event_id":"sha256:e253aa917b0b5ee44e519224e135dbf211028d788ed170009678d2290c3fc144"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:MZZZNCLA7DAOQ2QXRXLT3EJX24","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hilbert Space Embedding for Dirichlet Process Mixtures","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Krikamol Muandet","submitted_at":"2012-10-16T10:26:29Z","abstract_excerpt":"This paper proposes a Hilbert space embedding for Dirichlet Process mixture models via a stick-breaking construction of Sethuraman. Although Bayesian nonparametrics offers a powerful approach to construct a prior that avoids the need to specify the model size/complexity explicitly, an exact inference is often intractable. On the other hand, frequentist approaches such as kernel machines, which suffer from the model selection/comparison problems, often benefit from efficient learning algorithms. This paper discusses the possibility to combine the best of both worlds by using the Dirichlet Proce"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.4347","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":"2026-05-18T03:43:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wTT4V6jpcpURgsnf6v/4pws1s7CoLR6H7+9TWHXVGHr2+lqrPYCXL9i5RDBvKsOCMzfn8HOZo5trymBOoSCjAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:58:02.543714Z"},"content_sha256":"ad01c528905076592a00b33647b97cc0cdf15ca24e42e82254408660ed2069e7","schema_version":"1.0","event_id":"sha256:ad01c528905076592a00b33647b97cc0cdf15ca24e42e82254408660ed2069e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/bundle.json","state_url":"https://pith.science/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/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":"2026-05-27T00:58:02Z","links":{"resolver":"https://pith.science/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24","bundle":"https://pith.science/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/bundle.json","state":"https://pith.science/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MZZZNCLA7DAOQ2QXRXLT3EJX24/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:MZZZNCLA7DAOQ2QXRXLT3EJX24","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":"c9eeead29734594d3e8b3dd13ef7fd2163f82b44cd712cef22954edf991d60e9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-10-16T10:26:29Z","title_canon_sha256":"6be83edbe490250e304ddbdacd1f6925f6675dfc2a1f7a83ad71abbba8a74e48"},"schema_version":"1.0","source":{"id":"1210.4347","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1210.4347","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"arxiv_version","alias_value":"1210.4347v1","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1210.4347","created_at":"2026-05-18T03:43:06Z"},{"alias_kind":"pith_short_12","alias_value":"MZZZNCLA7DAO","created_at":"2026-05-18T12:27:16Z"},{"alias_kind":"pith_short_16","alias_value":"MZZZNCLA7DAOQ2QX","created_at":"2026-05-18T12:27:16Z"},{"alias_kind":"pith_short_8","alias_value":"MZZZNCLA","created_at":"2026-05-18T12:27:16Z"}],"graph_snapshots":[{"event_id":"sha256:ad01c528905076592a00b33647b97cc0cdf15ca24e42e82254408660ed2069e7","target":"graph","created_at":"2026-05-18T03:43:06Z","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":"This paper proposes a Hilbert space embedding for Dirichlet Process mixture models via a stick-breaking construction of Sethuraman. Although Bayesian nonparametrics offers a powerful approach to construct a prior that avoids the need to specify the model size/complexity explicitly, an exact inference is often intractable. On the other hand, frequentist approaches such as kernel machines, which suffer from the model selection/comparison problems, often benefit from efficient learning algorithms. This paper discusses the possibility to combine the best of both worlds by using the Dirichlet Proce","authors_text":"Krikamol Muandet","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-10-16T10:26:29Z","title":"Hilbert Space Embedding for Dirichlet Process Mixtures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1210.4347","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:e253aa917b0b5ee44e519224e135dbf211028d788ed170009678d2290c3fc144","target":"record","created_at":"2026-05-18T03:43:06Z","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":"c9eeead29734594d3e8b3dd13ef7fd2163f82b44cd712cef22954edf991d60e9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-10-16T10:26:29Z","title_canon_sha256":"6be83edbe490250e304ddbdacd1f6925f6675dfc2a1f7a83ad71abbba8a74e48"},"schema_version":"1.0","source":{"id":"1210.4347","kind":"arxiv","version":1}},"canonical_sha256":"6673968960f8c0e86a178dd73d9137d7269949758d2f50ce8e5770d251ead39a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6673968960f8c0e86a178dd73d9137d7269949758d2f50ce8e5770d251ead39a","first_computed_at":"2026-05-18T03:43:06.259144Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:43:06.259144Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pUqfFm1ThiFqJ3d/muHgMozyNSffKnaD6NDEqtBPW5AlIt0urLQsEmBhCnoYjIc45u3/0IXydmfptJDwVwZBBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T03:43:06.259845Z","signed_message":"canonical_sha256_bytes"},"source_id":"1210.4347","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e253aa917b0b5ee44e519224e135dbf211028d788ed170009678d2290c3fc144","sha256:ad01c528905076592a00b33647b97cc0cdf15ca24e42e82254408660ed2069e7"],"state_sha256":"749f3fce28d596fa43d1aa9ad641ccaa8a19deebf5728878fda013195818578c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G58ZFmX7BIzxqghHjZduXw7tuMW7q8lA/xZd7f7CDP6MMgo1Zwb1DMAJCGHYIblB9Y72Hv/GmR5e3D+EQuVeAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T00:58:02.546351Z","bundle_sha256":"36aa31ea45f817a894560ec2de7c5c132b8c5b81da874c96b6acb06daa207264"}}