{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:S66U77MSCEXXCMZ4ORGODLWR3F","short_pith_number":"pith:S66U77MS","canonical_record":{"source":{"id":"1609.06764","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-21T21:57:25Z","cross_cats_sorted":[],"title_canon_sha256":"df18cfc6ecb2ded638239bb095531190d2083cd9b8fa0f263c83b71c57065f8b","abstract_canon_sha256":"8ab6a332e5792630972f1c8c2e47b6e603d792c836ede05bb3dfac8ffb9a2998"},"schema_version":"1.0"},"canonical_sha256":"97bd4ffd92112f71333c744ce1aed1d962f5335d81489c5aa8560d0e1fb8f88b","source":{"kind":"arxiv","id":"1609.06764","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.06764","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"arxiv_version","alias_value":"1609.06764v3","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.06764","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"pith_short_12","alias_value":"S66U77MSCEXX","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_16","alias_value":"S66U77MSCEXXCMZ4","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_8","alias_value":"S66U77MS","created_at":"2026-05-18T12:30:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:S66U77MSCEXXCMZ4ORGODLWR3F","target":"record","payload":{"canonical_record":{"source":{"id":"1609.06764","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-21T21:57:25Z","cross_cats_sorted":[],"title_canon_sha256":"df18cfc6ecb2ded638239bb095531190d2083cd9b8fa0f263c83b71c57065f8b","abstract_canon_sha256":"8ab6a332e5792630972f1c8c2e47b6e603d792c836ede05bb3dfac8ffb9a2998"},"schema_version":"1.0"},"canonical_sha256":"97bd4ffd92112f71333c744ce1aed1d962f5335d81489c5aa8560d0e1fb8f88b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:29:01.860683Z","signature_b64":"tJ3nwMZR4OepHXzvXGgPsneAlkmwTtlwsEUkUpXkt3JDc2RWi0zQCChItmSvu+/4VijQMOwJlvF18/5TUIemDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97bd4ffd92112f71333c744ce1aed1d962f5335d81489c5aa8560d0e1fb8f88b","last_reissued_at":"2026-05-18T00:29:01.860087Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:29:01.860087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1609.06764","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EpsNqdasNcW8HQ3muak27+jzzcTCTTXEpdRnowgrY7exouWOjGp9/W9in3mTWBJTZClKW1Ri76vHSclxbUzcDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T09:53:11.882226Z"},"content_sha256":"068d39ae1d3b040ed698f87c0e990393745f2549b2f6c6ecaee5aa52d34a76a8","schema_version":"1.0","event_id":"sha256:068d39ae1d3b040ed698f87c0e990393745f2549b2f6c6ecaee5aa52d34a76a8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:S66U77MSCEXXCMZ4ORGODLWR3F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Saturating Splines and Feature Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Benjamin Recht, Michael Jordan, Nicholas Boyd, Stephen Boyd, Trevor Hastie","submitted_at":"2016-09-21T21:57:25Z","abstract_excerpt":"We extend the adaptive regression spline model by incorporating saturation, the natural requirement that a function extend as a constant outside a certain range. We fit saturating splines to data using a convex optimization problem over a space of measures, which we solve using an efficient algorithm based on the conditional gradient method. Unlike many existing approaches, our algorithm solves the original infinite-dimensional (for splines of degree at least two) optimization problem without pre-specified knot locations. We then adapt our algorithm to fit generalized additive models with satu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.06764","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:29:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7YumQAbfBqTDp5mZWEdxgy7deJJWkgFfMhLA0v1CaT8Y+0B2y5sT6OoUyoGZ+sRUvmbns7zPaeml3P5TM9clBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T09:53:11.882947Z"},"content_sha256":"a636d13c954214d376ae4d0ea9f4af78654619fdfd6fbaa26005ddca77a850c1","schema_version":"1.0","event_id":"sha256:a636d13c954214d376ae4d0ea9f4af78654619fdfd6fbaa26005ddca77a850c1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S66U77MSCEXXCMZ4ORGODLWR3F/bundle.json","state_url":"https://pith.science/pith/S66U77MSCEXXCMZ4ORGODLWR3F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S66U77MSCEXXCMZ4ORGODLWR3F/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":"2026-05-27T09:53:11Z","links":{"resolver":"https://pith.science/pith/S66U77MSCEXXCMZ4ORGODLWR3F","bundle":"https://pith.science/pith/S66U77MSCEXXCMZ4ORGODLWR3F/bundle.json","state":"https://pith.science/pith/S66U77MSCEXXCMZ4ORGODLWR3F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S66U77MSCEXXCMZ4ORGODLWR3F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:S66U77MSCEXXCMZ4ORGODLWR3F","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":"8ab6a332e5792630972f1c8c2e47b6e603d792c836ede05bb3dfac8ffb9a2998","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-21T21:57:25Z","title_canon_sha256":"df18cfc6ecb2ded638239bb095531190d2083cd9b8fa0f263c83b71c57065f8b"},"schema_version":"1.0","source":{"id":"1609.06764","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1609.06764","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"arxiv_version","alias_value":"1609.06764v3","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.06764","created_at":"2026-05-18T00:29:01Z"},{"alias_kind":"pith_short_12","alias_value":"S66U77MSCEXX","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_16","alias_value":"S66U77MSCEXXCMZ4","created_at":"2026-05-18T12:30:44Z"},{"alias_kind":"pith_short_8","alias_value":"S66U77MS","created_at":"2026-05-18T12:30:44Z"}],"graph_snapshots":[{"event_id":"sha256:a636d13c954214d376ae4d0ea9f4af78654619fdfd6fbaa26005ddca77a850c1","target":"graph","created_at":"2026-05-18T00:29:01Z","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 extend the adaptive regression spline model by incorporating saturation, the natural requirement that a function extend as a constant outside a certain range. We fit saturating splines to data using a convex optimization problem over a space of measures, which we solve using an efficient algorithm based on the conditional gradient method. Unlike many existing approaches, our algorithm solves the original infinite-dimensional (for splines of degree at least two) optimization problem without pre-specified knot locations. We then adapt our algorithm to fit generalized additive models with satu","authors_text":"Benjamin Recht, Michael Jordan, Nicholas Boyd, Stephen Boyd, Trevor Hastie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-21T21:57:25Z","title":"Saturating Splines and Feature Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.06764","kind":"arxiv","version":3},"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":"sha256:068d39ae1d3b040ed698f87c0e990393745f2549b2f6c6ecaee5aa52d34a76a8","target":"record","created_at":"2026-05-18T00:29:01Z","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":"8ab6a332e5792630972f1c8c2e47b6e603d792c836ede05bb3dfac8ffb9a2998","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-09-21T21:57:25Z","title_canon_sha256":"df18cfc6ecb2ded638239bb095531190d2083cd9b8fa0f263c83b71c57065f8b"},"schema_version":"1.0","source":{"id":"1609.06764","kind":"arxiv","version":3}},"canonical_sha256":"97bd4ffd92112f71333c744ce1aed1d962f5335d81489c5aa8560d0e1fb8f88b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97bd4ffd92112f71333c744ce1aed1d962f5335d81489c5aa8560d0e1fb8f88b","first_computed_at":"2026-05-18T00:29:01.860087Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:29:01.860087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tJ3nwMZR4OepHXzvXGgPsneAlkmwTtlwsEUkUpXkt3JDc2RWi0zQCChItmSvu+/4VijQMOwJlvF18/5TUIemDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:29:01.860683Z","signed_message":"canonical_sha256_bytes"},"source_id":"1609.06764","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:068d39ae1d3b040ed698f87c0e990393745f2549b2f6c6ecaee5aa52d34a76a8","sha256:a636d13c954214d376ae4d0ea9f4af78654619fdfd6fbaa26005ddca77a850c1"],"state_sha256":"7078799fc687cb694b408f6c68cd71ecfe609c727e46ffef7fa2c7dcbcd5f4db"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1KLHUlTt51i6Ao3ENUO9QeheRu6yjo7qWJn8wWahOZRR+FKgzDBvyGBpYayfnKrM+LAaLTaLddLbY5u4za4xCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T09:53:11.886875Z","bundle_sha256":"8d4337c61732b11116039d1bbe7d916a3ac1b8287546e7bfcb4ad8ec9eeb7ffc"}}