{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:IJLGQKMMGIYZBOYQ7NXDKCQSC5","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":"c1fbd0dbf6a4b6f8871e140055670b2a8c7ab64efd87fbe04ac43ba00ddd65dd","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-04-02T02:16:39Z","title_canon_sha256":"62302059f0233b7b9a1deac3fef1c74bc56c7546be1eefb1cd1e674660ec1987"},"schema_version":"1.0","source":{"id":"1504.00430","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1504.00430","created_at":"2026-05-18T02:19:43Z"},{"alias_kind":"arxiv_version","alias_value":"1504.00430v1","created_at":"2026-05-18T02:19:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1504.00430","created_at":"2026-05-18T02:19:43Z"},{"alias_kind":"pith_short_12","alias_value":"IJLGQKMMGIYZ","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_16","alias_value":"IJLGQKMMGIYZBOYQ","created_at":"2026-05-18T12:29:25Z"},{"alias_kind":"pith_short_8","alias_value":"IJLGQKMM","created_at":"2026-05-18T12:29:25Z"}],"graph_snapshots":[{"event_id":"sha256:123bafb17858db3e8a8bbbb722c47b5d2608fbb6ee6c9e6d8628a8da7d2352c0","target":"graph","created_at":"2026-05-18T02:19:43Z","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 this paper, we propose a novel sparse learning based feature selection method that directly optimizes a large margin linear classification model sparsity with l_(2,p)-norm (0 < p < 1)subject to data-fitting constraints, rather than using the sparsity as a regularization term. To solve the direct sparsity optimization problem that is non-smooth and non-convex when 0<p<1, we provide an efficient iterative algorithm with proved convergence by converting it to a convex and smooth optimization problem at every iteration step. The proposed algorithm has been evaluated based on publicly available ","authors_text":"Hanyang Peng, Yong Fan","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-04-02T02:16:39Z","title":"Direct l_(2,p)-Norm Learning for Feature Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1504.00430","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":"sha256:889d07a52be5887cd9cd8be6fae0ffec79934d8d657f61bd7599dda897965c00","target":"record","created_at":"2026-05-18T02:19:43Z","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":"c1fbd0dbf6a4b6f8871e140055670b2a8c7ab64efd87fbe04ac43ba00ddd65dd","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-04-02T02:16:39Z","title_canon_sha256":"62302059f0233b7b9a1deac3fef1c74bc56c7546be1eefb1cd1e674660ec1987"},"schema_version":"1.0","source":{"id":"1504.00430","kind":"arxiv","version":1}},"canonical_sha256":"425668298c323190bb10fb6e350a12175368bc9abf4f33e09b952070e6a6095d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"425668298c323190bb10fb6e350a12175368bc9abf4f33e09b952070e6a6095d","first_computed_at":"2026-05-18T02:19:43.341670Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:19:43.341670Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M6b4zBLsudULjrpEIqt4YhSXEGl6mSah3bUTMwAHx/zKKzvC69qwJ12iwinR9dF1M1Kan5LsZ6p3cy5LO7gnAA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:19:43.342107Z","signed_message":"canonical_sha256_bytes"},"source_id":"1504.00430","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:889d07a52be5887cd9cd8be6fae0ffec79934d8d657f61bd7599dda897965c00","sha256:123bafb17858db3e8a8bbbb722c47b5d2608fbb6ee6c9e6d8628a8da7d2352c0"],"state_sha256":"04f5a019ccc2d3a396d4f5597eada26f4396d67ba724b5ab134fa029b1e09987"}