{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:UVZTKVNSERAOWLFT3SLMTZHX7A","short_pith_number":"pith:UVZTKVNS","canonical_record":{"source":{"id":"1602.01951","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-05T08:27:27Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"ddbc43d90fe1a81f53c1ea6a5c419e1d1403183712595c02a62ea3463c93c704","abstract_canon_sha256":"70c7becf65ba0cef2b18fa246ab44d4b7d1bccdbe09fdf065b6b03acde5ca49c"},"schema_version":"1.0"},"canonical_sha256":"a5733555b22440eb2cb3dc96c9e4f7f82ca6be89be891c1131326d185bcf495a","source":{"kind":"arxiv","id":"1602.01951","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.01951","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"arxiv_version","alias_value":"1602.01951v1","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.01951","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"pith_short_12","alias_value":"UVZTKVNSERAO","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UVZTKVNSERAOWLFT","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UVZTKVNS","created_at":"2026-05-18T12:30:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:UVZTKVNSERAOWLFT3SLMTZHX7A","target":"record","payload":{"canonical_record":{"source":{"id":"1602.01951","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-05T08:27:27Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"ddbc43d90fe1a81f53c1ea6a5c419e1d1403183712595c02a62ea3463c93c704","abstract_canon_sha256":"70c7becf65ba0cef2b18fa246ab44d4b7d1bccdbe09fdf065b6b03acde5ca49c"},"schema_version":"1.0"},"canonical_sha256":"a5733555b22440eb2cb3dc96c9e4f7f82ca6be89be891c1131326d185bcf495a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:21:14.939969Z","signature_b64":"Ja3mKFZhqpX11KepASxJlKRT50YDMWKr/EodMwq12IN4iRdpHJaADrW9AK6zvLRtkcEwdrnhGq5NUej0f+p0Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a5733555b22440eb2cb3dc96c9e4f7f82ca6be89be891c1131326d185bcf495a","last_reissued_at":"2026-05-18T01:21:14.939417Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:21:14.939417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.01951","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":"2026-05-18T01:21:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/uEtwU/Q7JhfIyWf4BeN1hzp7rixZGtCzF9HBEC48A/NjaAYxyqqb5Ud48AscUvgEAbIutjma6dDhyApyhLOCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T12:36:52.807927Z"},"content_sha256":"d9511a47e7d5ae35a0342e6055322152fd103c11fc91160b7bd134295633dab6","schema_version":"1.0","event_id":"sha256:d9511a47e7d5ae35a0342e6055322152fd103c11fc91160b7bd134295633dab6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:UVZTKVNSERAOWLFT3SLMTZHX7A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Greedy algorithms for prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Alessio Sancetta","submitted_at":"2016-02-05T08:27:27Z","abstract_excerpt":"In many prediction problems, it is not uncommon that the number of variables used to construct a forecast is of the same order of magnitude as the sample size, if not larger. We then face the problem of constructing a prediction in the presence of potentially large estimation error. Control of the estimation error is either achieved by selecting variables or combining all the variables in some special way. This paper considers greedy algorithms to solve this problem. It is shown that the resulting estimators are consistent under weak conditions. In particular, the derived rates of convergence "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.01951","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":"2026-05-18T01:21:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FWYyrH494UyJY/P/947II52km+H2qJK+8QQ2tzNwLzMuMR12Pr+Lg1rvRCq7s2yLdRjq3Q4Iv+8RwDurxzy8Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T12:36:52.808787Z"},"content_sha256":"b213f31b4614d4284a8983f527039063ec54d05b2f014e9ed0270620da781a04","schema_version":"1.0","event_id":"sha256:b213f31b4614d4284a8983f527039063ec54d05b2f014e9ed0270620da781a04"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/bundle.json","state_url":"https://pith.science/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/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":"2026-05-30T12:36:52Z","links":{"resolver":"https://pith.science/pith/UVZTKVNSERAOWLFT3SLMTZHX7A","bundle":"https://pith.science/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/bundle.json","state":"https://pith.science/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UVZTKVNSERAOWLFT3SLMTZHX7A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:UVZTKVNSERAOWLFT3SLMTZHX7A","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":"70c7becf65ba0cef2b18fa246ab44d4b7d1bccdbe09fdf065b6b03acde5ca49c","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-05T08:27:27Z","title_canon_sha256":"ddbc43d90fe1a81f53c1ea6a5c419e1d1403183712595c02a62ea3463c93c704"},"schema_version":"1.0","source":{"id":"1602.01951","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.01951","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"arxiv_version","alias_value":"1602.01951v1","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.01951","created_at":"2026-05-18T01:21:14Z"},{"alias_kind":"pith_short_12","alias_value":"UVZTKVNSERAO","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UVZTKVNSERAOWLFT","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UVZTKVNS","created_at":"2026-05-18T12:30:46Z"}],"graph_snapshots":[{"event_id":"sha256:b213f31b4614d4284a8983f527039063ec54d05b2f014e9ed0270620da781a04","target":"graph","created_at":"2026-05-18T01:21:14Z","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 many prediction problems, it is not uncommon that the number of variables used to construct a forecast is of the same order of magnitude as the sample size, if not larger. We then face the problem of constructing a prediction in the presence of potentially large estimation error. Control of the estimation error is either achieved by selecting variables or combining all the variables in some special way. This paper considers greedy algorithms to solve this problem. It is shown that the resulting estimators are consistent under weak conditions. In particular, the derived rates of convergence ","authors_text":"Alessio Sancetta","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-05T08:27:27Z","title":"Greedy algorithms for prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.01951","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:d9511a47e7d5ae35a0342e6055322152fd103c11fc91160b7bd134295633dab6","target":"record","created_at":"2026-05-18T01:21:14Z","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":"70c7becf65ba0cef2b18fa246ab44d4b7d1bccdbe09fdf065b6b03acde5ca49c","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2016-02-05T08:27:27Z","title_canon_sha256":"ddbc43d90fe1a81f53c1ea6a5c419e1d1403183712595c02a62ea3463c93c704"},"schema_version":"1.0","source":{"id":"1602.01951","kind":"arxiv","version":1}},"canonical_sha256":"a5733555b22440eb2cb3dc96c9e4f7f82ca6be89be891c1131326d185bcf495a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5733555b22440eb2cb3dc96c9e4f7f82ca6be89be891c1131326d185bcf495a","first_computed_at":"2026-05-18T01:21:14.939417Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:21:14.939417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ja3mKFZhqpX11KepASxJlKRT50YDMWKr/EodMwq12IN4iRdpHJaADrW9AK6zvLRtkcEwdrnhGq5NUej0f+p0Dg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:21:14.939969Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.01951","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d9511a47e7d5ae35a0342e6055322152fd103c11fc91160b7bd134295633dab6","sha256:b213f31b4614d4284a8983f527039063ec54d05b2f014e9ed0270620da781a04"],"state_sha256":"fec635a4e40c9c6862e5bf15f61e6921cfe8c4beb626b75e3d534ca639ecea36"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GvjwzCJiFd8+a76T+MhCsO+sN9IVMxTAPrfuth+seCegHkf+jBuUrblsBPoSO/rsb0s//0ChjRE05PdskhPkBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T12:36:52.812882Z","bundle_sha256":"868d0b0fbfc82d900e7268dbdc97fcc60179925ea1fb5298b80dbe8291b529b4"}}