{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:KF5T7WZS2XR3A6QB7ZPKVEYIL2","short_pith_number":"pith:KF5T7WZS","schema_version":"1.0","canonical_sha256":"517b3fdb32d5e3b07a01fe5eaa93085e8687f33985a9e83a1722fdd9f4ef4445","source":{"kind":"arxiv","id":"2606.01554","version":1},"attestation_state":"computed","paper":{"title":"Fast Near-Optimal Estimation over Symmetric Norm Balls","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Matey Neykov","submitted_at":"2026-06-01T01:58:28Z","abstract_excerpt":"This short note proposes a polynomial-time algorithm for near-optimal Euclidean estimation of a signal constrained to lie in the unit ball of a symmetric norm, where the symmetry is with respect to a known basis and the norm is accessible through an evaluation oracle. We further extend the method to a random-design, moderate-dimensional linear regression setting, where the regression parameter is likewise assumed to belong to a constraint set defined by a symmetric norm."},"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":"2606.01554","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-01T01:58:28Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"472fe27bc6055310f00f643efad573a76540a7dd2050441851a9077786e1ee65","abstract_canon_sha256":"650acbe5865bb6d8fa8ffd1e6f8e0d67a7e164aaf2213ba53deab338df84358a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T02:04:36.271282Z","signature_b64":"1cIblpOUpiJYXMQXq6vVLdmeXoqeGvQIP/aipYiCfvIRf2yg8zGSpIFKzWZIdXvzjM82ghg4cR2lhgt+90q5Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"517b3fdb32d5e3b07a01fe5eaa93085e8687f33985a9e83a1722fdd9f4ef4445","last_reissued_at":"2026-06-02T02:04:36.270907Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T02:04:36.270907Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fast Near-Optimal Estimation over Symmetric Norm Balls","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Matey Neykov","submitted_at":"2026-06-01T01:58:28Z","abstract_excerpt":"This short note proposes a polynomial-time algorithm for near-optimal Euclidean estimation of a signal constrained to lie in the unit ball of a symmetric norm, where the symmetry is with respect to a known basis and the norm is accessible through an evaluation oracle. We further extend the method to a random-design, moderate-dimensional linear regression setting, where the regression parameter is likewise assumed to belong to a constraint set defined by a symmetric norm."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01554","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.01554/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2606.01554","created_at":"2026-06-02T02:04:36.270964+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.01554v1","created_at":"2026-06-02T02:04:36.270964+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01554","created_at":"2026-06-02T02:04:36.270964+00:00"},{"alias_kind":"pith_short_12","alias_value":"KF5T7WZS2XR3","created_at":"2026-06-02T02:04:36.270964+00:00"},{"alias_kind":"pith_short_16","alias_value":"KF5T7WZS2XR3A6QB","created_at":"2026-06-02T02:04:36.270964+00:00"},{"alias_kind":"pith_short_8","alias_value":"KF5T7WZS","created_at":"2026-06-02T02:04:36.270964+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/KF5T7WZS2XR3A6QB7ZPKVEYIL2","json":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2.json","graph_json":"https://pith.science/api/pith-number/KF5T7WZS2XR3A6QB7ZPKVEYIL2/graph.json","events_json":"https://pith.science/api/pith-number/KF5T7WZS2XR3A6QB7ZPKVEYIL2/events.json","paper":"https://pith.science/paper/KF5T7WZS"},"agent_actions":{"view_html":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2","download_json":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2.json","view_paper":"https://pith.science/paper/KF5T7WZS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.01554&json=true","fetch_graph":"https://pith.science/api/pith-number/KF5T7WZS2XR3A6QB7ZPKVEYIL2/graph.json","fetch_events":"https://pith.science/api/pith-number/KF5T7WZS2XR3A6QB7ZPKVEYIL2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2/action/storage_attestation","attest_author":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2/action/author_attestation","sign_citation":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2/action/citation_signature","submit_replication":"https://pith.science/pith/KF5T7WZS2XR3A6QB7ZPKVEYIL2/action/replication_record"}},"created_at":"2026-06-02T02:04:36.270964+00:00","updated_at":"2026-06-02T02:04:36.270964+00:00"}