{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:QTQIHF5BWMPTMMR5RYZ22A5E6S","short_pith_number":"pith:QTQIHF5B","canonical_record":{"source":{"id":"1809.02860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-08T19:40:14Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"04d122c7e4345fff907405a7fdc0f3cd12acd8c883c0c9534d093a57cd529bb3","abstract_canon_sha256":"9ebef49094cf6faf6f449d2ce094c6bd46d23d9a3b7ae0275ccb739ac15a37a7"},"schema_version":"1.0"},"canonical_sha256":"84e08397a1b31f36323d8e33ad03a4f499871cb3290bae46dff41da1eeb57a6e","source":{"kind":"arxiv","id":"1809.02860","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.02860","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"arxiv_version","alias_value":"1809.02860v1","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.02860","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"pith_short_12","alias_value":"QTQIHF5BWMPT","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QTQIHF5BWMPTMMR5","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QTQIHF5B","created_at":"2026-05-18T12:32:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:QTQIHF5BWMPTMMR5RYZ22A5E6S","target":"record","payload":{"canonical_record":{"source":{"id":"1809.02860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-08T19:40:14Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"04d122c7e4345fff907405a7fdc0f3cd12acd8c883c0c9534d093a57cd529bb3","abstract_canon_sha256":"9ebef49094cf6faf6f449d2ce094c6bd46d23d9a3b7ae0275ccb739ac15a37a7"},"schema_version":"1.0"},"canonical_sha256":"84e08397a1b31f36323d8e33ad03a4f499871cb3290bae46dff41da1eeb57a6e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:06:15.089861Z","signature_b64":"GuSZniqR1gOXNZPyTnSMo7O/vFHdnSMjn5Hcj59XPPVq9D5WlLOO1tFyo+CHzBgUk4lzyUDCr4waJ2KPMsYSDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"84e08397a1b31f36323d8e33ad03a4f499871cb3290bae46dff41da1eeb57a6e","last_reissued_at":"2026-05-18T00:06:15.089233Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:06:15.089233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.02860","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":"2026-05-18T00:06:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RJ+Hukh9g7un6DeKhtcrk23lQ59Lm8n0mSRCgaoXtf6HI5M/9bViZLTLhD3iN9+gYM74Zrnf1/J2PIq3qTBXBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T18:00:32.647926Z"},"content_sha256":"544dfe661151e0cde975b8229de42fefe335b1263fc6d06555f3c73b1cc38cfd","schema_version":"1.0","event_id":"sha256:544dfe661151e0cde975b8229de42fefe335b1263fc6d06555f3c73b1cc38cfd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:QTQIHF5BWMPTMMR5RYZ22A5E6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Identifying The Most Informative Features Using A Structurally Interacting Elastic Net","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Edwin R. Hancock, Lixin Cui, Lu Bai, Yue Wang, Zhihong Zhang","submitted_at":"2018-09-08T19:40:14Z","abstract_excerpt":"Feature selection can efficiently identify the most informative features with respect to the target feature used in training. However, state-of-the-art vector-based methods are unable to encapsulate the relationships between feature samples into the feature selection process, thus leading to significant information loss. To address this problem, we propose a new graph-based structurally interacting elastic net method for feature selection. Specifically, we commence by constructing feature graphs that can incorporate pairwise relationship between samples. With the feature graphs to hand, we pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.02860","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":"2026-05-18T00:06:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L27VfoiXkHf0zrObQCKzvzMyRywmrCZ8nIGqnEBzuiiUAdgM46HVsxCJEUt4+gk7rrqlXXzjhzMbpUxkGMLIAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T18:00:32.648275Z"},"content_sha256":"185b3bc8de7e73716e74cc90a38413c17dc5114f94f000b4aba6af8a54fc7ff4","schema_version":"1.0","event_id":"sha256:185b3bc8de7e73716e74cc90a38413c17dc5114f94f000b4aba6af8a54fc7ff4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/bundle.json","state_url":"https://pith.science/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/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":"2026-06-01T18:00:32Z","links":{"resolver":"https://pith.science/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S","bundle":"https://pith.science/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/bundle.json","state":"https://pith.science/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QTQIHF5BWMPTMMR5RYZ22A5E6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:QTQIHF5BWMPTMMR5RYZ22A5E6S","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":"9ebef49094cf6faf6f449d2ce094c6bd46d23d9a3b7ae0275ccb739ac15a37a7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-08T19:40:14Z","title_canon_sha256":"04d122c7e4345fff907405a7fdc0f3cd12acd8c883c0c9534d093a57cd529bb3"},"schema_version":"1.0","source":{"id":"1809.02860","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.02860","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"arxiv_version","alias_value":"1809.02860v1","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.02860","created_at":"2026-05-18T00:06:15Z"},{"alias_kind":"pith_short_12","alias_value":"QTQIHF5BWMPT","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_16","alias_value":"QTQIHF5BWMPTMMR5","created_at":"2026-05-18T12:32:46Z"},{"alias_kind":"pith_short_8","alias_value":"QTQIHF5B","created_at":"2026-05-18T12:32:46Z"}],"graph_snapshots":[{"event_id":"sha256:185b3bc8de7e73716e74cc90a38413c17dc5114f94f000b4aba6af8a54fc7ff4","target":"graph","created_at":"2026-05-18T00:06:15Z","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":"Feature selection can efficiently identify the most informative features with respect to the target feature used in training. However, state-of-the-art vector-based methods are unable to encapsulate the relationships between feature samples into the feature selection process, thus leading to significant information loss. To address this problem, we propose a new graph-based structurally interacting elastic net method for feature selection. Specifically, we commence by constructing feature graphs that can incorporate pairwise relationship between samples. With the feature graphs to hand, we pro","authors_text":"Edwin R. Hancock, Lixin Cui, Lu Bai, Yue Wang, Zhihong Zhang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-08T19:40:14Z","title":"Identifying The Most Informative Features Using A Structurally Interacting Elastic Net"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.02860","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":"sha256:544dfe661151e0cde975b8229de42fefe335b1263fc6d06555f3c73b1cc38cfd","target":"record","created_at":"2026-05-18T00:06:15Z","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":"9ebef49094cf6faf6f449d2ce094c6bd46d23d9a3b7ae0275ccb739ac15a37a7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-08T19:40:14Z","title_canon_sha256":"04d122c7e4345fff907405a7fdc0f3cd12acd8c883c0c9534d093a57cd529bb3"},"schema_version":"1.0","source":{"id":"1809.02860","kind":"arxiv","version":1}},"canonical_sha256":"84e08397a1b31f36323d8e33ad03a4f499871cb3290bae46dff41da1eeb57a6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"84e08397a1b31f36323d8e33ad03a4f499871cb3290bae46dff41da1eeb57a6e","first_computed_at":"2026-05-18T00:06:15.089233Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:06:15.089233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GuSZniqR1gOXNZPyTnSMo7O/vFHdnSMjn5Hcj59XPPVq9D5WlLOO1tFyo+CHzBgUk4lzyUDCr4waJ2KPMsYSDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:06:15.089861Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.02860","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:544dfe661151e0cde975b8229de42fefe335b1263fc6d06555f3c73b1cc38cfd","sha256:185b3bc8de7e73716e74cc90a38413c17dc5114f94f000b4aba6af8a54fc7ff4"],"state_sha256":"e22dbf42ac9ebfba63ce14d008bcde64238874055e3dad784525a7be9ed7fc26"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IzO1vV1qvjG2XCGw9tkgloX8h7Xn4fUehDnXzHZotxDlwiuMUEXrAHWe3XxOiYM+3Tx+CZcfqzPbmdk6oEzVAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T18:00:32.650249Z","bundle_sha256":"806276481d58cc41b7c6614d20eed8a44b1ec6c429ef5f5093af30252dc6288d"}}