{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:67I2IZT55YXYEUB46HCUEULVYH","short_pith_number":"pith:67I2IZT5","schema_version":"1.0","canonical_sha256":"f7d1a4667dee2f82503cf1c5425175c1f10d1c2c8614b65f14d3c3e24efdded1","source":{"kind":"arxiv","id":"1305.0626","version":1},"attestation_state":"computed","paper":{"title":"An Improved EM algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Fuqiang Chen","submitted_at":"2013-05-03T06:25:41Z","abstract_excerpt":"In this paper, we firstly give a brief introduction of expectation maximization (EM) algorithm, and then discuss the initial value sensitivity of expectation maximization algorithm. Subsequently, we give a short proof of EM's convergence. Then, we implement experiments with the expectation maximization algorithm (We implement all the experiments on Gaussion mixture model (GMM)). Our experiment with expectation maximization is performed in the following three cases: initialize randomly; initialize with result of K-means; initialize with result of K-medoids. The experiment result shows that expe"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1305.0626","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-05-03T06:25:41Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"1fb673ad7d346434376544e5dce48c90d06a840ebe8c08af92aca4a679865029","abstract_canon_sha256":"e9c39debf50cc5303ca174a56a1ede2e57e2623688b81390a297f9b3cdd59c90"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:26:33.166245Z","signature_b64":"mIJfMEXsMrUWUmeS1RC/2NecE57eTL0Y8HARSK9V41ufuc/PANh60vJpgsm5M2lneG/GDBBrBjhrdrgZrSa8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7d1a4667dee2f82503cf1c5425175c1f10d1c2c8614b65f14d3c3e24efdded1","last_reissued_at":"2026-05-18T03:26:33.165832Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:26:33.165832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Improved EM algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Fuqiang Chen","submitted_at":"2013-05-03T06:25:41Z","abstract_excerpt":"In this paper, we firstly give a brief introduction of expectation maximization (EM) algorithm, and then discuss the initial value sensitivity of expectation maximization algorithm. Subsequently, we give a short proof of EM's convergence. Then, we implement experiments with the expectation maximization algorithm (We implement all the experiments on Gaussion mixture model (GMM)). Our experiment with expectation maximization is performed in the following three cases: initialize randomly; initialize with result of K-means; initialize with result of K-medoids. The experiment result shows that expe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1305.0626","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1305.0626","created_at":"2026-05-18T03:26:33.165897+00:00"},{"alias_kind":"arxiv_version","alias_value":"1305.0626v1","created_at":"2026-05-18T03:26:33.165897+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1305.0626","created_at":"2026-05-18T03:26:33.165897+00:00"},{"alias_kind":"pith_short_12","alias_value":"67I2IZT55YXY","created_at":"2026-05-18T12:27:36.564083+00:00"},{"alias_kind":"pith_short_16","alias_value":"67I2IZT55YXYEUB4","created_at":"2026-05-18T12:27:36.564083+00:00"},{"alias_kind":"pith_short_8","alias_value":"67I2IZT5","created_at":"2026-05-18T12:27:36.564083+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH","json":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH.json","graph_json":"https://pith.science/api/pith-number/67I2IZT55YXYEUB46HCUEULVYH/graph.json","events_json":"https://pith.science/api/pith-number/67I2IZT55YXYEUB46HCUEULVYH/events.json","paper":"https://pith.science/paper/67I2IZT5"},"agent_actions":{"view_html":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH","download_json":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH.json","view_paper":"https://pith.science/paper/67I2IZT5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1305.0626&json=true","fetch_graph":"https://pith.science/api/pith-number/67I2IZT55YXYEUB46HCUEULVYH/graph.json","fetch_events":"https://pith.science/api/pith-number/67I2IZT55YXYEUB46HCUEULVYH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH/action/storage_attestation","attest_author":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH/action/author_attestation","sign_citation":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH/action/citation_signature","submit_replication":"https://pith.science/pith/67I2IZT55YXYEUB46HCUEULVYH/action/replication_record"}},"created_at":"2026-05-18T03:26:33.165897+00:00","updated_at":"2026-05-18T03:26:33.165897+00:00"}