{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:OMREILFTDZ3IWQ2NZ7JINN73JC","short_pith_number":"pith:OMREILFT","schema_version":"1.0","canonical_sha256":"7322442cb31e768b434dcfd286b7fb488366a43dc7995325c36fc68baf42f878","source":{"kind":"arxiv","id":"1703.01332","version":3},"attestation_state":"computed","paper":{"title":"Optimistic lower bounds for convex regularized least-squares","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Pierre C Bellec","submitted_at":"2017-03-03T20:33:58Z","abstract_excerpt":"Minimax lower bounds are pessimistic in nature: for any given estimator, minimax lower bounds yield the existence of a worst-case target vector $\\beta^*_{worst}$ for which the prediction error of the given estimator is bounded from below. However, minimax lower bounds shed no light on the prediction error of the given estimator for target vectors different than $\\beta^*_{worst}$. A characterization of the prediction error of any convex regularized least-squares is given. This characterization provide both a lower bound and an upper bound on the prediction error. This produces lower bounds that"},"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":"1703.01332","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2017-03-03T20:33:58Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"fe32375e8d7d6a5368f0babf9a722981bd4d6e2c8acd65ee281be20c3946138b","abstract_canon_sha256":"9ab0b34891445ae2efdb013c494f6712a82d9209b08b9532b5a3881ae3f36acd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:32.220238Z","signature_b64":"GeLfLGT9GNVCZnxb8wWdtDJ1ozL4X1q426QnKb5hSF2sC5GBS2bhEE5V+G/nbtzv6Nrnu3eyTtTQy9CpCUhiCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7322442cb31e768b434dcfd286b7fb488366a43dc7995325c36fc68baf42f878","last_reissued_at":"2026-05-18T00:33:32.219725Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:32.219725Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimistic lower bounds for convex regularized least-squares","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Pierre C Bellec","submitted_at":"2017-03-03T20:33:58Z","abstract_excerpt":"Minimax lower bounds are pessimistic in nature: for any given estimator, minimax lower bounds yield the existence of a worst-case target vector $\\beta^*_{worst}$ for which the prediction error of the given estimator is bounded from below. However, minimax lower bounds shed no light on the prediction error of the given estimator for target vectors different than $\\beta^*_{worst}$. A characterization of the prediction error of any convex regularized least-squares is given. This characterization provide both a lower bound and an upper bound on the prediction error. This produces lower bounds that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.01332","kind":"arxiv","version":3},"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":"1703.01332","created_at":"2026-05-18T00:33:32.219807+00:00"},{"alias_kind":"arxiv_version","alias_value":"1703.01332v3","created_at":"2026-05-18T00:33:32.219807+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.01332","created_at":"2026-05-18T00:33:32.219807+00:00"},{"alias_kind":"pith_short_12","alias_value":"OMREILFTDZ3I","created_at":"2026-05-18T12:31:34.259226+00:00"},{"alias_kind":"pith_short_16","alias_value":"OMREILFTDZ3IWQ2N","created_at":"2026-05-18T12:31:34.259226+00:00"},{"alias_kind":"pith_short_8","alias_value":"OMREILFT","created_at":"2026-05-18T12:31:34.259226+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/OMREILFTDZ3IWQ2NZ7JINN73JC","json":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC.json","graph_json":"https://pith.science/api/pith-number/OMREILFTDZ3IWQ2NZ7JINN73JC/graph.json","events_json":"https://pith.science/api/pith-number/OMREILFTDZ3IWQ2NZ7JINN73JC/events.json","paper":"https://pith.science/paper/OMREILFT"},"agent_actions":{"view_html":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC","download_json":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC.json","view_paper":"https://pith.science/paper/OMREILFT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1703.01332&json=true","fetch_graph":"https://pith.science/api/pith-number/OMREILFTDZ3IWQ2NZ7JINN73JC/graph.json","fetch_events":"https://pith.science/api/pith-number/OMREILFTDZ3IWQ2NZ7JINN73JC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC/action/storage_attestation","attest_author":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC/action/author_attestation","sign_citation":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC/action/citation_signature","submit_replication":"https://pith.science/pith/OMREILFTDZ3IWQ2NZ7JINN73JC/action/replication_record"}},"created_at":"2026-05-18T00:33:32.219807+00:00","updated_at":"2026-05-18T00:33:32.219807+00:00"}