{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:FBGF2YXAQU2SIVLEOGRSXSBH3Q","short_pith_number":"pith:FBGF2YXA","schema_version":"1.0","canonical_sha256":"284c5d62e0853524556471a32bc827dc33adc4960c4209bddc1a70400f174bc0","source":{"kind":"arxiv","id":"1304.6663","version":2},"attestation_state":"computed","paper":{"title":"Low-rank optimization for distance matrix completion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"math.OC","authors_text":"B. Mishra, G. Meyer, R. Sepulchre","submitted_at":"2013-04-24T16:52:34Z","abstract_excerpt":"This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. Th"},"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":"1304.6663","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2013-04-24T16:52:34Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"999e67d0d5a61f8fad8d64e8ef62da31dc6e4771f01238414c902dffb690fb29","abstract_canon_sha256":"5c60ea33e9d0d3ec03d50644b075fd49e19eab68e55c6356f8a86ff225e2c579"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:27:11.034815Z","signature_b64":"mmvEzAJcDyL2lN7tJeb+/KDbXh7eHrSrjO03I4txlWNZb2Wn7BOn/UrWw1E2PR+GlaucBcU8YtM5v3AIqDgjAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"284c5d62e0853524556471a32bc827dc33adc4960c4209bddc1a70400f174bc0","last_reissued_at":"2026-05-18T03:27:11.034199Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:27:11.034199Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Low-rank optimization for distance matrix completion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"math.OC","authors_text":"B. Mishra, G. Meyer, R. Sepulchre","submitted_at":"2013-04-24T16:52:34Z","abstract_excerpt":"This paper addresses the problem of low-rank distance matrix completion. This problem amounts to recover the missing entries of a distance matrix when the dimension of the data embedding space is possibly unknown but small compared to the number of considered data points. The focus is on high-dimensional problems. We recast the considered problem into an optimization problem over the set of low-rank positive semidefinite matrices and propose two efficient algorithms for low-rank distance matrix completion. In addition, we propose a strategy to determine the dimension of the embedding space. Th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.6663","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1304.6663","created_at":"2026-05-18T03:27:11.034279+00:00"},{"alias_kind":"arxiv_version","alias_value":"1304.6663v2","created_at":"2026-05-18T03:27:11.034279+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.6663","created_at":"2026-05-18T03:27:11.034279+00:00"},{"alias_kind":"pith_short_12","alias_value":"FBGF2YXAQU2S","created_at":"2026-05-18T12:27:45.050594+00:00"},{"alias_kind":"pith_short_16","alias_value":"FBGF2YXAQU2SIVLE","created_at":"2026-05-18T12:27:45.050594+00:00"},{"alias_kind":"pith_short_8","alias_value":"FBGF2YXA","created_at":"2026-05-18T12:27:45.050594+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/FBGF2YXAQU2SIVLEOGRSXSBH3Q","json":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q.json","graph_json":"https://pith.science/api/pith-number/FBGF2YXAQU2SIVLEOGRSXSBH3Q/graph.json","events_json":"https://pith.science/api/pith-number/FBGF2YXAQU2SIVLEOGRSXSBH3Q/events.json","paper":"https://pith.science/paper/FBGF2YXA"},"agent_actions":{"view_html":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q","download_json":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q.json","view_paper":"https://pith.science/paper/FBGF2YXA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1304.6663&json=true","fetch_graph":"https://pith.science/api/pith-number/FBGF2YXAQU2SIVLEOGRSXSBH3Q/graph.json","fetch_events":"https://pith.science/api/pith-number/FBGF2YXAQU2SIVLEOGRSXSBH3Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q/action/storage_attestation","attest_author":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q/action/author_attestation","sign_citation":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q/action/citation_signature","submit_replication":"https://pith.science/pith/FBGF2YXAQU2SIVLEOGRSXSBH3Q/action/replication_record"}},"created_at":"2026-05-18T03:27:11.034279+00:00","updated_at":"2026-05-18T03:27:11.034279+00:00"}