{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:DQ65545RPZG57R4RC4APFLY6P5","short_pith_number":"pith:DQ65545R","canonical_record":{"source":{"id":"1903.04631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-03-11T22:14:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2f7faad679437ff73828bb1dbb88283ae1b42cd2547c75bab060e9f2db4652dd","abstract_canon_sha256":"ad674c05597dddf4bcbeed9b246e06f1b8dd9e4cf989e4fb516022ea0508830f"},"schema_version":"1.0"},"canonical_sha256":"1c3ddef3b17e4ddfc7911700f2af1e7f4b092ac634c00b3eb2c92f05a8a04ec9","source":{"kind":"arxiv","id":"1903.04631","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.04631","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"arxiv_version","alias_value":"1903.04631v1","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.04631","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"pith_short_12","alias_value":"DQ65545RPZG5","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"DQ65545RPZG57R4R","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"DQ65545R","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:DQ65545RPZG57R4RC4APFLY6P5","target":"record","payload":{"canonical_record":{"source":{"id":"1903.04631","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-03-11T22:14:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2f7faad679437ff73828bb1dbb88283ae1b42cd2547c75bab060e9f2db4652dd","abstract_canon_sha256":"ad674c05597dddf4bcbeed9b246e06f1b8dd9e4cf989e4fb516022ea0508830f"},"schema_version":"1.0"},"canonical_sha256":"1c3ddef3b17e4ddfc7911700f2af1e7f4b092ac634c00b3eb2c92f05a8a04ec9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:29.094175Z","signature_b64":"kdunXOCChOgedFqXXLHgEQSx6nPbuTxBFaNc0wMuXQFHWe9IWwCprRESiVFh+HbcQKL+LrNLnMi9p4odSOx+BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c3ddef3b17e4ddfc7911700f2af1e7f4b092ac634c00b3eb2c92f05a8a04ec9","last_reissued_at":"2026-05-17T23:51:29.093760Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:29.093760Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.04631","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:51:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HPghHOu46xW4ZjKgq3hfnIu6alIv03qO4qTgD/3zbwf3AfnNIgPsBAb37ZKR6lCFMj5U896eMDrvE+uWlNZXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:22:38.838959Z"},"content_sha256":"3b95f55643dbdd5b390ed589213ac1723de504126e648fe4b65c3785862e467e","schema_version":"1.0","event_id":"sha256:3b95f55643dbdd5b390ed589213ac1723de504126e648fe4b65c3785862e467e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:DQ65545RPZG57R4RC4APFLY6P5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Wavelet regression and additive models for irregularly spaced data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Ali Shojaie, Asad Haris, Noah Simon","submitted_at":"2019-03-11T22:14:40Z","abstract_excerpt":"We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, $\\texttt{waveMesh}$, can be applied to non-equispaced data with sample size not necessarily a power of 2. We develop an efficient proximal gradient descent algorithm for computing the estimator and establish adaptive minimax convergence rates. The main appeal of our approach is that it naturally extends to additive and sparse additive models for a potentially large number of covariates. We prove minimax optimal convergence rates under a weak compatibility condition for sparse additive models. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.04631","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":""},"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":"2026-05-17T23:51:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ASGKo80WgAgecGW36Bid4sP9r5ECII4Ij/cSNabml72oEgvJkaSUGASouXg7tHBMUpa9I1Wm02uJNALKS4ajBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:22:38.839621Z"},"content_sha256":"0733794b802dcd02864f62adeda4e441df156845c16d4ed8056abc68f7676478","schema_version":"1.0","event_id":"sha256:0733794b802dcd02864f62adeda4e441df156845c16d4ed8056abc68f7676478"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DQ65545RPZG57R4RC4APFLY6P5/bundle.json","state_url":"https://pith.science/pith/DQ65545RPZG57R4RC4APFLY6P5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DQ65545RPZG57R4RC4APFLY6P5/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":"2026-05-26T15:22:38Z","links":{"resolver":"https://pith.science/pith/DQ65545RPZG57R4RC4APFLY6P5","bundle":"https://pith.science/pith/DQ65545RPZG57R4RC4APFLY6P5/bundle.json","state":"https://pith.science/pith/DQ65545RPZG57R4RC4APFLY6P5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DQ65545RPZG57R4RC4APFLY6P5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:DQ65545RPZG57R4RC4APFLY6P5","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":"ad674c05597dddf4bcbeed9b246e06f1b8dd9e4cf989e4fb516022ea0508830f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-03-11T22:14:40Z","title_canon_sha256":"2f7faad679437ff73828bb1dbb88283ae1b42cd2547c75bab060e9f2db4652dd"},"schema_version":"1.0","source":{"id":"1903.04631","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.04631","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"arxiv_version","alias_value":"1903.04631v1","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.04631","created_at":"2026-05-17T23:51:29Z"},{"alias_kind":"pith_short_12","alias_value":"DQ65545RPZG5","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"DQ65545RPZG57R4R","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"DQ65545R","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:0733794b802dcd02864f62adeda4e441df156845c16d4ed8056abc68f7676478","target":"graph","created_at":"2026-05-17T23:51:29Z","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":"We present a novel approach for nonparametric regression using wavelet basis functions. Our proposal, $\\texttt{waveMesh}$, can be applied to non-equispaced data with sample size not necessarily a power of 2. We develop an efficient proximal gradient descent algorithm for computing the estimator and establish adaptive minimax convergence rates. The main appeal of our approach is that it naturally extends to additive and sparse additive models for a potentially large number of covariates. We prove minimax optimal convergence rates under a weak compatibility condition for sparse additive models. ","authors_text":"Ali Shojaie, Asad Haris, Noah Simon","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-03-11T22:14:40Z","title":"Wavelet regression and additive models for irregularly spaced data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.04631","kind":"arxiv","version":1},"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":"sha256:3b95f55643dbdd5b390ed589213ac1723de504126e648fe4b65c3785862e467e","target":"record","created_at":"2026-05-17T23:51:29Z","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":"ad674c05597dddf4bcbeed9b246e06f1b8dd9e4cf989e4fb516022ea0508830f","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-03-11T22:14:40Z","title_canon_sha256":"2f7faad679437ff73828bb1dbb88283ae1b42cd2547c75bab060e9f2db4652dd"},"schema_version":"1.0","source":{"id":"1903.04631","kind":"arxiv","version":1}},"canonical_sha256":"1c3ddef3b17e4ddfc7911700f2af1e7f4b092ac634c00b3eb2c92f05a8a04ec9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c3ddef3b17e4ddfc7911700f2af1e7f4b092ac634c00b3eb2c92f05a8a04ec9","first_computed_at":"2026-05-17T23:51:29.093760Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:29.093760Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kdunXOCChOgedFqXXLHgEQSx6nPbuTxBFaNc0wMuXQFHWe9IWwCprRESiVFh+HbcQKL+LrNLnMi9p4odSOx+BQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:29.094175Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.04631","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b95f55643dbdd5b390ed589213ac1723de504126e648fe4b65c3785862e467e","sha256:0733794b802dcd02864f62adeda4e441df156845c16d4ed8056abc68f7676478"],"state_sha256":"599c4b23c978aa46a97270dcbb7ce7bb79f6d3b2eaf2118d79ff107d4fde9253"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aEaORSw0qP3VMg65JFpP7JLikXfjdKgLtFuxW4PiFkSC8OcJ2WGCuRYvL2iBFNQZ7AczGMcnaVPN9v+IyslwDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T15:22:38.843123Z","bundle_sha256":"388a4fd7d90395207f7450f010d2f20241bd167bf9f96f58f20b8667ad6bdec0"}}