{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:5ENFXVJKWKBUQZUPDIW7QIWEO5","short_pith_number":"pith:5ENFXVJK","schema_version":"1.0","canonical_sha256":"e91a5bd52ab28348668f1a2df822c477612f3abe53f3180be5f7964db276f7c9","source":{"kind":"arxiv","id":"1012.1886","version":2},"attestation_state":"computed","paper":{"title":"Sublinear Time, Measurement-Optimal, Sparse Recovery For All","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Ely Porat, Martin J. Strauss","submitted_at":"2010-12-08T22:39:52Z","abstract_excerpt":"An approximate sparse recovery system in ell_1 norm formally consists of parameters N, k, epsilon an m-by-N measurement matrix, Phi, and a decoding algorithm, D. Given a vector, x, where x_k denotes the optimal k-term approximation to x, the system approximates x by hat_x = D(Phi.x), which must satisfy\n  ||hat_x - x||_1 <= (1+epsilon)||x - x_k||_1.\n  Among the goals in designing such systems are minimizing m and the runtime of D. We consider the \"forall\" model, in which a single matrix Phi is used for all signals x.\n  All previous algorithms that use the optimal number m=O(k log(N/k)) of measu"},"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":"1012.1886","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2010-12-08T22:39:52Z","cross_cats_sorted":[],"title_canon_sha256":"f70fde5f663c4678644b7654abf28723e7a611dabbab04845d952bb14b94bf30","abstract_canon_sha256":"67f9bfb257f82899a3c9a60ef44c909e90572c8781ae491652865357dded5632"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:18:22.189930Z","signature_b64":"PeNskuBaYRSpWpzCVBdKxlxVFlak2fI9FdpVqV8PihN8+zjSPbqKVNv+u6ikk/W4BzXlaYg1UBpqKuMzK1YXAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e91a5bd52ab28348668f1a2df822c477612f3abe53f3180be5f7964db276f7c9","last_reissued_at":"2026-05-18T04:18:22.189490Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:18:22.189490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Sublinear Time, Measurement-Optimal, Sparse Recovery For All","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Ely Porat, Martin J. Strauss","submitted_at":"2010-12-08T22:39:52Z","abstract_excerpt":"An approximate sparse recovery system in ell_1 norm formally consists of parameters N, k, epsilon an m-by-N measurement matrix, Phi, and a decoding algorithm, D. Given a vector, x, where x_k denotes the optimal k-term approximation to x, the system approximates x by hat_x = D(Phi.x), which must satisfy\n  ||hat_x - x||_1 <= (1+epsilon)||x - x_k||_1.\n  Among the goals in designing such systems are minimizing m and the runtime of D. We consider the \"forall\" model, in which a single matrix Phi is used for all signals x.\n  All previous algorithms that use the optimal number m=O(k log(N/k)) of measu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1012.1886","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":"1012.1886","created_at":"2026-05-18T04:18:22.189564+00:00"},{"alias_kind":"arxiv_version","alias_value":"1012.1886v2","created_at":"2026-05-18T04:18:22.189564+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1012.1886","created_at":"2026-05-18T04:18:22.189564+00:00"},{"alias_kind":"pith_short_12","alias_value":"5ENFXVJKWKBU","created_at":"2026-05-18T12:26:04.259169+00:00"},{"alias_kind":"pith_short_16","alias_value":"5ENFXVJKWKBUQZUP","created_at":"2026-05-18T12:26:04.259169+00:00"},{"alias_kind":"pith_short_8","alias_value":"5ENFXVJK","created_at":"2026-05-18T12:26:04.259169+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/5ENFXVJKWKBUQZUPDIW7QIWEO5","json":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5.json","graph_json":"https://pith.science/api/pith-number/5ENFXVJKWKBUQZUPDIW7QIWEO5/graph.json","events_json":"https://pith.science/api/pith-number/5ENFXVJKWKBUQZUPDIW7QIWEO5/events.json","paper":"https://pith.science/paper/5ENFXVJK"},"agent_actions":{"view_html":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5","download_json":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5.json","view_paper":"https://pith.science/paper/5ENFXVJK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1012.1886&json=true","fetch_graph":"https://pith.science/api/pith-number/5ENFXVJKWKBUQZUPDIW7QIWEO5/graph.json","fetch_events":"https://pith.science/api/pith-number/5ENFXVJKWKBUQZUPDIW7QIWEO5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5/action/storage_attestation","attest_author":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5/action/author_attestation","sign_citation":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5/action/citation_signature","submit_replication":"https://pith.science/pith/5ENFXVJKWKBUQZUPDIW7QIWEO5/action/replication_record"}},"created_at":"2026-05-18T04:18:22.189564+00:00","updated_at":"2026-05-18T04:18:22.189564+00:00"}