{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:PCWKKHQOP62S2GDXRN43KD4L2N","short_pith_number":"pith:PCWKKHQO","canonical_record":{"source":{"id":"1811.10411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T02:30:59Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"3b681af5e50c1506c4ca018742692ef80067bf08c568a60917705334738d1cd6","abstract_canon_sha256":"6b410c6078d712dc0cc941a0f1638d94b97704b26d2448506b854e6adb1061a0"},"schema_version":"1.0"},"canonical_sha256":"78aca51e0e7fb52d18778b79b50f8bd37379823baad812fb2d19fcf67544aa79","source":{"kind":"arxiv","id":"1811.10411","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10411","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10411v2","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10411","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"pith_short_12","alias_value":"PCWKKHQOP62S","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PCWKKHQOP62S2GDX","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PCWKKHQO","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:PCWKKHQOP62S2GDXRN43KD4L2N","target":"record","payload":{"canonical_record":{"source":{"id":"1811.10411","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T02:30:59Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"3b681af5e50c1506c4ca018742692ef80067bf08c568a60917705334738d1cd6","abstract_canon_sha256":"6b410c6078d712dc0cc941a0f1638d94b97704b26d2448506b854e6adb1061a0"},"schema_version":"1.0"},"canonical_sha256":"78aca51e0e7fb52d18778b79b50f8bd37379823baad812fb2d19fcf67544aa79","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:52.480797Z","signature_b64":"t//gEu/jg9H4Jz2o4nLTK/vGBjs7ILqO3dXeGuwjePwON58kIqOlUr3JXZ0wIvletDFNWaJPemTk2PwdnL9oAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"78aca51e0e7fb52d18778b79b50f8bd37379823baad812fb2d19fcf67544aa79","last_reissued_at":"2026-05-17T23:45:52.480355Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:52.480355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.10411","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:45:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ywBz6h3vrI1GKVJgC8sTo132cHjAhthy9cA1wPPd9Uw3s1lKAzaSNezD+vfahgEM9O/Gk4YSy5WlAeypJ3tjDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:00:37.878923Z"},"content_sha256":"0e37d9612b0424cb2d6dd1ac3d363938af8dd0b4e5aaf17e47e6398325417e89","schema_version":"1.0","event_id":"sha256:0e37d9612b0424cb2d6dd1ac3d363938af8dd0b4e5aaf17e47e6398325417e89"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:PCWKKHQOP62S2GDXRN43KD4L2N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Minimax adaptive wavelet estimator for the anisotropic functional deconvolution model with unknown kernel","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Qing Liu, Rida Benhaddou","submitted_at":"2018-11-22T02:30:59Z","abstract_excerpt":"In the present paper, we consider the estimation of a periodic two-dimensional function $f(\\cdot,\\cdot)$ based on observations from its noisy convolution, and convolution kernel $g(\\cdot,\\cdot)$ unknown. We derive the minimax lower bounds for the mean squared error assuming that $f$ belongs to certain Besov space and the kernel function $g$ satisfies some smoothness properties. We construct an adaptive hard-thresholding wavelet estimator that is asymptotically near-optimal within a logarithmic factor in a wide range of Besov balls. The proposed estimation algorithm implements a truncation to e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10411","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:45:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2Fk21Ke8JbW3jIPo0YK5Av9+5TyZzD//GAmAk9QcuiUlw3UbpANNbQ8zsZFWOx1vqB5vQoTSO4vTVAIS7VClDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T14:00:37.879253Z"},"content_sha256":"fef4ab45df5c6acfc329f46f5b6ffe4486ceb9f54f5be24c684588d97dc9b02c","schema_version":"1.0","event_id":"sha256:fef4ab45df5c6acfc329f46f5b6ffe4486ceb9f54f5be24c684588d97dc9b02c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PCWKKHQOP62S2GDXRN43KD4L2N/bundle.json","state_url":"https://pith.science/pith/PCWKKHQOP62S2GDXRN43KD4L2N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PCWKKHQOP62S2GDXRN43KD4L2N/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-30T14:00:37Z","links":{"resolver":"https://pith.science/pith/PCWKKHQOP62S2GDXRN43KD4L2N","bundle":"https://pith.science/pith/PCWKKHQOP62S2GDXRN43KD4L2N/bundle.json","state":"https://pith.science/pith/PCWKKHQOP62S2GDXRN43KD4L2N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PCWKKHQOP62S2GDXRN43KD4L2N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:PCWKKHQOP62S2GDXRN43KD4L2N","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":"6b410c6078d712dc0cc941a0f1638d94b97704b26d2448506b854e6adb1061a0","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T02:30:59Z","title_canon_sha256":"3b681af5e50c1506c4ca018742692ef80067bf08c568a60917705334738d1cd6"},"schema_version":"1.0","source":{"id":"1811.10411","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.10411","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"arxiv_version","alias_value":"1811.10411v2","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.10411","created_at":"2026-05-17T23:45:52Z"},{"alias_kind":"pith_short_12","alias_value":"PCWKKHQOP62S","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"PCWKKHQOP62S2GDX","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"PCWKKHQO","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:fef4ab45df5c6acfc329f46f5b6ffe4486ceb9f54f5be24c684588d97dc9b02c","target":"graph","created_at":"2026-05-17T23:45:52Z","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 the present paper, we consider the estimation of a periodic two-dimensional function $f(\\cdot,\\cdot)$ based on observations from its noisy convolution, and convolution kernel $g(\\cdot,\\cdot)$ unknown. We derive the minimax lower bounds for the mean squared error assuming that $f$ belongs to certain Besov space and the kernel function $g$ satisfies some smoothness properties. We construct an adaptive hard-thresholding wavelet estimator that is asymptotically near-optimal within a logarithmic factor in a wide range of Besov balls. The proposed estimation algorithm implements a truncation to e","authors_text":"Qing Liu, Rida Benhaddou","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T02:30:59Z","title":"Minimax adaptive wavelet estimator for the anisotropic functional deconvolution model with unknown kernel"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.10411","kind":"arxiv","version":2},"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":"sha256:0e37d9612b0424cb2d6dd1ac3d363938af8dd0b4e5aaf17e47e6398325417e89","target":"record","created_at":"2026-05-17T23:45:52Z","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":"6b410c6078d712dc0cc941a0f1638d94b97704b26d2448506b854e6adb1061a0","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-22T02:30:59Z","title_canon_sha256":"3b681af5e50c1506c4ca018742692ef80067bf08c568a60917705334738d1cd6"},"schema_version":"1.0","source":{"id":"1811.10411","kind":"arxiv","version":2}},"canonical_sha256":"78aca51e0e7fb52d18778b79b50f8bd37379823baad812fb2d19fcf67544aa79","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"78aca51e0e7fb52d18778b79b50f8bd37379823baad812fb2d19fcf67544aa79","first_computed_at":"2026-05-17T23:45:52.480355Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:52.480355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t//gEu/jg9H4Jz2o4nLTK/vGBjs7ILqO3dXeGuwjePwON58kIqOlUr3JXZ0wIvletDFNWaJPemTk2PwdnL9oAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:52.480797Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.10411","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e37d9612b0424cb2d6dd1ac3d363938af8dd0b4e5aaf17e47e6398325417e89","sha256:fef4ab45df5c6acfc329f46f5b6ffe4486ceb9f54f5be24c684588d97dc9b02c"],"state_sha256":"e28ed16e9cd782d99f578a0d23ed6d7ac9c40aa731d4ab71798277e108af806d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9zxZwXSOlD5zgMSRW6AkIGGaX1yCRx6bPJz1ZYiIT7biaxZ+AEgHyH+jRxy7wAr4qc1+pDj1eli0BXqDuLkJBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T14:00:37.881148Z","bundle_sha256":"fb6084345f61511cc5c091cf9310700ffaaaf8fa3735e6ed86bab22b2a5feefe"}}