{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:WZUPTKYF4ZQWEO2YZC4IE5PKV7","short_pith_number":"pith:WZUPTKYF","schema_version":"1.0","canonical_sha256":"b668f9ab05e661623b58c8b88275eaafef503c791408d55024638b73e7b350a4","source":{"kind":"arxiv","id":"1410.2505","version":2},"attestation_state":"computed","paper":{"title":"Recovery of Sparse Signals Using Multiple Orthogonal Least Squares","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"stat.ME","authors_text":"Jian Wang, Ping Li","submitted_at":"2014-10-09T15:17:54Z","abstract_excerpt":"We study the problem of recovering sparse signals from compressed linear measurements. This problem, often referred to as sparse recovery or sparse reconstruction, has generated a great deal of interest in recent years. To recover the sparse signals, we propose a new method called multiple orthogonal least squares (MOLS), which extends the well-known orthogonal least squares (OLS) algorithm by allowing multiple $L$ indices to be chosen per iteration. Owing to inclusion of multiple support indices in each selection, the MOLS algorithm converges in much fewer iterations and improves the computat"},"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":"1410.2505","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2014-10-09T15:17:54Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"title_canon_sha256":"8e7714e677e9908d59c8dc588c2e10bc8bfb4f12214f13c64e353e49307a9ba1","abstract_canon_sha256":"a4382d81c7f8f1d643fe7cd0cc7bfe90179f3c94924c60dd580abff889cc32b9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:23:33.728188Z","signature_b64":"V4V1Wfh5Gut/WijVMUllsiiS9q5/QzULIx6xs1dBfZOLg1cWQ3HUneiH98LIgPw5R4gjbC6qecgJwVB8x5whCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b668f9ab05e661623b58c8b88275eaafef503c791408d55024638b73e7b350a4","last_reissued_at":"2026-05-18T01:23:33.727484Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:23:33.727484Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Recovery of Sparse Signals Using Multiple Orthogonal Least Squares","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"stat.ME","authors_text":"Jian Wang, Ping Li","submitted_at":"2014-10-09T15:17:54Z","abstract_excerpt":"We study the problem of recovering sparse signals from compressed linear measurements. This problem, often referred to as sparse recovery or sparse reconstruction, has generated a great deal of interest in recent years. To recover the sparse signals, we propose a new method called multiple orthogonal least squares (MOLS), which extends the well-known orthogonal least squares (OLS) algorithm by allowing multiple $L$ indices to be chosen per iteration. Owing to inclusion of multiple support indices in each selection, the MOLS algorithm converges in much fewer iterations and improves the computat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.2505","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":"1410.2505","created_at":"2026-05-18T01:23:33.727595+00:00"},{"alias_kind":"arxiv_version","alias_value":"1410.2505v2","created_at":"2026-05-18T01:23:33.727595+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.2505","created_at":"2026-05-18T01:23:33.727595+00:00"},{"alias_kind":"pith_short_12","alias_value":"WZUPTKYF4ZQW","created_at":"2026-05-18T12:28:54.890064+00:00"},{"alias_kind":"pith_short_16","alias_value":"WZUPTKYF4ZQWEO2Y","created_at":"2026-05-18T12:28:54.890064+00:00"},{"alias_kind":"pith_short_8","alias_value":"WZUPTKYF","created_at":"2026-05-18T12:28:54.890064+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/WZUPTKYF4ZQWEO2YZC4IE5PKV7","json":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7.json","graph_json":"https://pith.science/api/pith-number/WZUPTKYF4ZQWEO2YZC4IE5PKV7/graph.json","events_json":"https://pith.science/api/pith-number/WZUPTKYF4ZQWEO2YZC4IE5PKV7/events.json","paper":"https://pith.science/paper/WZUPTKYF"},"agent_actions":{"view_html":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7","download_json":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7.json","view_paper":"https://pith.science/paper/WZUPTKYF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1410.2505&json=true","fetch_graph":"https://pith.science/api/pith-number/WZUPTKYF4ZQWEO2YZC4IE5PKV7/graph.json","fetch_events":"https://pith.science/api/pith-number/WZUPTKYF4ZQWEO2YZC4IE5PKV7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7/action/storage_attestation","attest_author":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7/action/author_attestation","sign_citation":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7/action/citation_signature","submit_replication":"https://pith.science/pith/WZUPTKYF4ZQWEO2YZC4IE5PKV7/action/replication_record"}},"created_at":"2026-05-18T01:23:33.727595+00:00","updated_at":"2026-05-18T01:23:33.727595+00:00"}