{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:TRMXXWRHMRQLBKVOXFZXJWLBUD","short_pith_number":"pith:TRMXXWRH","canonical_record":{"source":{"id":"1301.3851","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:49:54Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3c55f9d5f7d483c73ff50eefe8cdf01794450c8ec963d2e05b627e0784919167","abstract_canon_sha256":"32942ab3896120567e29ee04cec00c1e94f5b9be0aaa8717bb9969c82353adae"},"schema_version":"1.0"},"canonical_sha256":"9c597bda276460b0aaaeb97374d961a0c7937f2a2e0b244af70327ab40b17414","source":{"kind":"arxiv","id":"1301.3851","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3851","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3851v1","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3851","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"pith_short_12","alias_value":"TRMXXWRHMRQL","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"TRMXXWRHMRQLBKVO","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"TRMXXWRH","created_at":"2026-05-18T12:28:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:TRMXXWRHMRQLBKVOXFZXJWLBUD","target":"record","payload":{"canonical_record":{"source":{"id":"1301.3851","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:49:54Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3c55f9d5f7d483c73ff50eefe8cdf01794450c8ec963d2e05b627e0784919167","abstract_canon_sha256":"32942ab3896120567e29ee04cec00c1e94f5b9be0aaa8717bb9969c82353adae"},"schema_version":"1.0"},"canonical_sha256":"9c597bda276460b0aaaeb97374d961a0c7937f2a2e0b244af70327ab40b17414","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:36:15.352221Z","signature_b64":"ScD6xSyUUklcHKdI+VEDJg5bVTJhwph5U6n0dahatYQfnOZbhcT43A66r1Fjv2yOnKX7zJwG5jX/WzhlYua7CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c597bda276460b0aaaeb97374d961a0c7937f2a2e0b244af70327ab40b17414","last_reissued_at":"2026-05-18T03:36:15.351666Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:36:15.351666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.3851","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":"2026-05-18T03:36:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aN5bZF6dOPdbmBlUoXUX/67MevoRtZ9Tkzoja1SRzhkE8WhSmh/4vcfW9I7weqYLUTwvmm0nTx1ffHU0zbVJBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T23:42:10.073376Z"},"content_sha256":"130d5f25c8caf2c92e1db88a44aecf886e7bc360975973c435643f02ec128366","schema_version":"1.0","event_id":"sha256:130d5f25c8caf2c92e1db88a44aecf886e7bc360975973c435643f02ec128366"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:TRMXXWRHMRQLBKVOXFZXJWLBUD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Minimum Message Length Clustering Using Gibbs Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Ian Davidson","submitted_at":"2013-01-16T15:49:54Z","abstract_excerpt":"The K-Mean and EM algorithms are popular in clustering and mixture modeling, due to their simplicity and ease of implementation. However, they have several significant limitations. Both coverage to a local optimum of their respective objective functions (ignoring the uncertainty in the model space), require the apriori specification of the number of classes/clsuters, and are inconsistent.  In this work we overcome these limitations by using the Minimum Message Length (MML) principle and a variation to the K-Means/EM observation assignment and parameter calculation scheme.  We maintain the simp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3851","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":"2026-05-18T03:36:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+vDeaaWTveSFoIHeevbfD/+JTubqL977dWWHnhloTidSvwhqU9S9vpw9jKFhXv3mZWy8vpM2qMuejMNxTu9pAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T23:42:10.074006Z"},"content_sha256":"d4984d17cd19ff2ee46af89a7e127e2f716dd2ab8d19d6c8825a3631e9e48b6e","schema_version":"1.0","event_id":"sha256:d4984d17cd19ff2ee46af89a7e127e2f716dd2ab8d19d6c8825a3631e9e48b6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/bundle.json","state_url":"https://pith.science/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/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":"2026-05-29T23:42:10Z","links":{"resolver":"https://pith.science/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD","bundle":"https://pith.science/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/bundle.json","state":"https://pith.science/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TRMXXWRHMRQLBKVOXFZXJWLBUD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:TRMXXWRHMRQLBKVOXFZXJWLBUD","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":"32942ab3896120567e29ee04cec00c1e94f5b9be0aaa8717bb9969c82353adae","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:49:54Z","title_canon_sha256":"3c55f9d5f7d483c73ff50eefe8cdf01794450c8ec963d2e05b627e0784919167"},"schema_version":"1.0","source":{"id":"1301.3851","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3851","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3851v1","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3851","created_at":"2026-05-18T03:36:15Z"},{"alias_kind":"pith_short_12","alias_value":"TRMXXWRHMRQL","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"TRMXXWRHMRQLBKVO","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"TRMXXWRH","created_at":"2026-05-18T12:28:02Z"}],"graph_snapshots":[{"event_id":"sha256:d4984d17cd19ff2ee46af89a7e127e2f716dd2ab8d19d6c8825a3631e9e48b6e","target":"graph","created_at":"2026-05-18T03:36:15Z","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"},"paper":{"abstract_excerpt":"The K-Mean and EM algorithms are popular in clustering and mixture modeling, due to their simplicity and ease of implementation. However, they have several significant limitations. Both coverage to a local optimum of their respective objective functions (ignoring the uncertainty in the model space), require the apriori specification of the number of classes/clsuters, and are inconsistent.  In this work we overcome these limitations by using the Minimum Message Length (MML) principle and a variation to the K-Means/EM observation assignment and parameter calculation scheme.  We maintain the simp","authors_text":"Ian Davidson","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:49:54Z","title":"Minimum Message Length Clustering Using Gibbs Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3851","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":"sha256:130d5f25c8caf2c92e1db88a44aecf886e7bc360975973c435643f02ec128366","target":"record","created_at":"2026-05-18T03:36:15Z","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":"32942ab3896120567e29ee04cec00c1e94f5b9be0aaa8717bb9969c82353adae","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T15:49:54Z","title_canon_sha256":"3c55f9d5f7d483c73ff50eefe8cdf01794450c8ec963d2e05b627e0784919167"},"schema_version":"1.0","source":{"id":"1301.3851","kind":"arxiv","version":1}},"canonical_sha256":"9c597bda276460b0aaaeb97374d961a0c7937f2a2e0b244af70327ab40b17414","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c597bda276460b0aaaeb97374d961a0c7937f2a2e0b244af70327ab40b17414","first_computed_at":"2026-05-18T03:36:15.351666Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:36:15.351666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ScD6xSyUUklcHKdI+VEDJg5bVTJhwph5U6n0dahatYQfnOZbhcT43A66r1Fjv2yOnKX7zJwG5jX/WzhlYua7CQ==","signature_status":"signed_v1","signed_at":"2026-05-18T03:36:15.352221Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.3851","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:130d5f25c8caf2c92e1db88a44aecf886e7bc360975973c435643f02ec128366","sha256:d4984d17cd19ff2ee46af89a7e127e2f716dd2ab8d19d6c8825a3631e9e48b6e"],"state_sha256":"8dc745fbf61a1125e97763c3a963675504f151771a9f046f7cf0a4454c020274"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/VaGYyPU4+ZjmfcQLjLOnPUbqmAzg4014drubD7wCE3bfCnSWiUXp8++XglHWEobg9fUpZrCmMRVP3o4iCpJCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T23:42:10.078262Z","bundle_sha256":"59bcc71f25e79816172e287b927ea95a64de08bd82b8ba7c002119afe7006a5b"}}