{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:ELDOQTBQCGBWV4VPLH4LXDJ4Q5","short_pith_number":"pith:ELDOQTBQ","schema_version":"1.0","canonical_sha256":"22c6e84c3011836af2af59f8bb8d3c875220797d1aca3cfa4e7ffae7aa62f2d2","source":{"kind":"arxiv","id":"1508.03337","version":5},"attestation_state":"computed","paper":{"title":"A Randomized Rounding Algorithm for Sparse PCA","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.DS","authors_text":"Abhisek Kundu, Eugenia-Maria Kontopoulou, Kimon Fountoulakis, Petros Drineas","submitted_at":"2015-08-13T20:06:59Z","abstract_excerpt":"We present and analyze a simple, two-step algorithm to approximate the optimal solution of the sparse PCA problem. Our approach first solves a L1 penalized version of the NP-hard sparse PCA optimization problem and then uses a randomized rounding strategy to sparsify the resulting dense solution. Our main theoretical result guarantees an additive error approximation and provides a tradeoff between sparsity and accuracy. Our experimental evaluation indicates that our approach is competitive in practice, even compared to state-of-the-art toolboxes such as Spasm."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1508.03337","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2015-08-13T20:06:59Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"72f3e2a972fba1d964b20cb134782ec248b61800fbb2387c042a91979a726b3b","abstract_canon_sha256":"3fecbd9dccb36c538aacf848aad3ff257abbe0e37f5820045960f61cb4862150"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:57:04.888914Z","signature_b64":"RIdzCreS5++koE3lFVOulVVqFweSflDjc/oLr4IAadNlvFr573dlQvnTLIOXr62qWykzoLD2UphQL7HiWO9ZCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22c6e84c3011836af2af59f8bb8d3c875220797d1aca3cfa4e7ffae7aa62f2d2","last_reissued_at":"2026-05-18T00:57:04.888312Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:57:04.888312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Randomized Rounding Algorithm for Sparse PCA","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.DS","authors_text":"Abhisek Kundu, Eugenia-Maria Kontopoulou, Kimon Fountoulakis, Petros Drineas","submitted_at":"2015-08-13T20:06:59Z","abstract_excerpt":"We present and analyze a simple, two-step algorithm to approximate the optimal solution of the sparse PCA problem. Our approach first solves a L1 penalized version of the NP-hard sparse PCA optimization problem and then uses a randomized rounding strategy to sparsify the resulting dense solution. Our main theoretical result guarantees an additive error approximation and provides a tradeoff between sparsity and accuracy. Our experimental evaluation indicates that our approach is competitive in practice, even compared to state-of-the-art toolboxes such as Spasm."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.03337","kind":"arxiv","version":5},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1508.03337","created_at":"2026-05-18T00:57:04.888403+00:00"},{"alias_kind":"arxiv_version","alias_value":"1508.03337v5","created_at":"2026-05-18T00:57:04.888403+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.03337","created_at":"2026-05-18T00:57:04.888403+00:00"},{"alias_kind":"pith_short_12","alias_value":"ELDOQTBQCGBW","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_16","alias_value":"ELDOQTBQCGBWV4VP","created_at":"2026-05-18T12:29:19.899920+00:00"},{"alias_kind":"pith_short_8","alias_value":"ELDOQTBQ","created_at":"2026-05-18T12:29:19.899920+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5","json":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5.json","graph_json":"https://pith.science/api/pith-number/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/graph.json","events_json":"https://pith.science/api/pith-number/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/events.json","paper":"https://pith.science/paper/ELDOQTBQ"},"agent_actions":{"view_html":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5","download_json":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5.json","view_paper":"https://pith.science/paper/ELDOQTBQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1508.03337&json=true","fetch_graph":"https://pith.science/api/pith-number/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/graph.json","fetch_events":"https://pith.science/api/pith-number/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/action/storage_attestation","attest_author":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/action/author_attestation","sign_citation":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/action/citation_signature","submit_replication":"https://pith.science/pith/ELDOQTBQCGBWV4VPLH4LXDJ4Q5/action/replication_record"}},"created_at":"2026-05-18T00:57:04.888403+00:00","updated_at":"2026-05-18T00:57:04.888403+00:00"}