{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GZSLIMSSW35CA5MFHX6OVAY4SB","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":"08b06ce563ca7d4302715fb066e8f1f6722e13ee2613c26c0aa5065752a2fc5c","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2018-11-21T15:20:18Z","title_canon_sha256":"ac42738f9f86212bd3dae0a0a3e5456fa54814647c950160c9d48fb146569a72"},"schema_version":"1.0","source":{"id":"1811.08778","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.08778","created_at":"2026-05-17T23:45:09Z"},{"alias_kind":"arxiv_version","alias_value":"1811.08778v3","created_at":"2026-05-17T23:45:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.08778","created_at":"2026-05-17T23:45:09Z"},{"alias_kind":"pith_short_12","alias_value":"GZSLIMSSW35C","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GZSLIMSSW35CA5MF","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GZSLIMSS","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:cc200b2f1690176c8debf8b5f8c3ba25abf2c34a31d6039528a98dc651b9d2b2","target":"graph","created_at":"2026-05-17T23:45:09Z","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":"In this paper, we consider the challenge of reconstructing jointly sparse vectors from linear measurements. Firstly, we show that by utilizing the rank of the output data matrix we can reduce the problem to a full column rank case. This result reveals a reduction in the computational complexity of the original problem and enables a simple implementation of joint sparse recovery algorithms for full-rank setting. Secondly, we propose a new method for joint sparse recovery in the form of a non-convex optimization problem on a non-compact Stiefel manifold. In our numerical experiments our method o","authors_text":"Armenak Petrosyan, Clayton Webster, Hoang Tran","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2018-11-21T15:20:18Z","title":"Reconstruction of jointly sparse vectors via manifold optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.08778","kind":"arxiv","version":3},"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":"sha256:724d9f9c391124edf01a7ceae505343dd2382870685ece6f1364ea5183393a41","target":"record","created_at":"2026-05-17T23:45:09Z","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":"08b06ce563ca7d4302715fb066e8f1f6722e13ee2613c26c0aa5065752a2fc5c","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.NA","submitted_at":"2018-11-21T15:20:18Z","title_canon_sha256":"ac42738f9f86212bd3dae0a0a3e5456fa54814647c950160c9d48fb146569a72"},"schema_version":"1.0","source":{"id":"1811.08778","kind":"arxiv","version":3}},"canonical_sha256":"3664b43252b6fa2075853dfcea831c904c8f85da76a345cbf123ac244a627728","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3664b43252b6fa2075853dfcea831c904c8f85da76a345cbf123ac244a627728","first_computed_at":"2026-05-17T23:45:09.379299Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:09.379299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kQKSu85yWRlu+ByIhzpea1ndOQHEt35VQpFgfkhI8en5loHkRf4xQgzUewETUqj8rnFLbr27qFcLr3uDcswMBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:09.380069Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.08778","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:724d9f9c391124edf01a7ceae505343dd2382870685ece6f1364ea5183393a41","sha256:cc200b2f1690176c8debf8b5f8c3ba25abf2c34a31d6039528a98dc651b9d2b2"],"state_sha256":"98a6ef22cf917f3a86fbe03d7c662ac098c7ad31d40542032beecafca99bd42c"}