{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:7IP44RXGUX6ECUQPKYAPHFTJE6","short_pith_number":"pith:7IP44RXG","schema_version":"1.0","canonical_sha256":"fa1fce46e6a5fc41520f5600f39669279d30686c3b4ed69be0587c62ecfda7ed","source":{"kind":"arxiv","id":"1409.2902","version":1},"attestation_state":"computed","paper":{"title":"The Hildreth's Algorithm with Applications to Soft Constraints for User Interface Layout","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"cs.NA","authors_text":"Alex Cloninger, Noreen Jamil, Xuemei Chen","submitted_at":"2014-09-09T21:16:56Z","abstract_excerpt":"The Hildreth's algorithm is a row action method for solving large systems of inequalities. This algorithm is efficient for problems with sparse matrices, as opposed to direct methods such as Gaussian elimination or QR-factorization. We apply the Hildreth's algorithm, as well as a randomized version, along with prioritized selection of the inequalities, to efficiently detect the highest priority feasible subsystem of equations. We prove convergence results and feasibility criteria for both cyclic and randomized Hildreth's algorithm, as well as a mixed algorithm which uses Hildreth's algorithm f"},"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":"1409.2902","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2014-09-09T21:16:56Z","cross_cats_sorted":["math.NA"],"title_canon_sha256":"3af82580d833969d683f7839d5aa0cba1e1998ed86f99d32f35f29a39312ddc5","abstract_canon_sha256":"3ec9fdf17d3a0cffcc3e73f42e18b5b7fbdce373c0cef5c076a08c04c311eea3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:43:08.789547Z","signature_b64":"/Dudbt2Xi5/NJRnMpN9uah12bq/wZAXlbRNioGiwvnktFktXiInPIPeOgw7eQ+AJ20aNKUBQAzqlAbOpd++5Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa1fce46e6a5fc41520f5600f39669279d30686c3b4ed69be0587c62ecfda7ed","last_reissued_at":"2026-05-18T02:43:08.789084Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:43:08.789084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Hildreth's Algorithm with Applications to Soft Constraints for User Interface Layout","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.NA"],"primary_cat":"cs.NA","authors_text":"Alex Cloninger, Noreen Jamil, Xuemei Chen","submitted_at":"2014-09-09T21:16:56Z","abstract_excerpt":"The Hildreth's algorithm is a row action method for solving large systems of inequalities. This algorithm is efficient for problems with sparse matrices, as opposed to direct methods such as Gaussian elimination or QR-factorization. We apply the Hildreth's algorithm, as well as a randomized version, along with prioritized selection of the inequalities, to efficiently detect the highest priority feasible subsystem of equations. We prove convergence results and feasibility criteria for both cyclic and randomized Hildreth's algorithm, as well as a mixed algorithm which uses Hildreth's algorithm f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.2902","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1409.2902","created_at":"2026-05-18T02:43:08.789154+00:00"},{"alias_kind":"arxiv_version","alias_value":"1409.2902v1","created_at":"2026-05-18T02:43:08.789154+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.2902","created_at":"2026-05-18T02:43:08.789154+00:00"},{"alias_kind":"pith_short_12","alias_value":"7IP44RXGUX6E","created_at":"2026-05-18T12:28:19.803747+00:00"},{"alias_kind":"pith_short_16","alias_value":"7IP44RXGUX6ECUQP","created_at":"2026-05-18T12:28:19.803747+00:00"},{"alias_kind":"pith_short_8","alias_value":"7IP44RXG","created_at":"2026-05-18T12:28:19.803747+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/7IP44RXGUX6ECUQPKYAPHFTJE6","json":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6.json","graph_json":"https://pith.science/api/pith-number/7IP44RXGUX6ECUQPKYAPHFTJE6/graph.json","events_json":"https://pith.science/api/pith-number/7IP44RXGUX6ECUQPKYAPHFTJE6/events.json","paper":"https://pith.science/paper/7IP44RXG"},"agent_actions":{"view_html":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6","download_json":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6.json","view_paper":"https://pith.science/paper/7IP44RXG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1409.2902&json=true","fetch_graph":"https://pith.science/api/pith-number/7IP44RXGUX6ECUQPKYAPHFTJE6/graph.json","fetch_events":"https://pith.science/api/pith-number/7IP44RXGUX6ECUQPKYAPHFTJE6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6/action/storage_attestation","attest_author":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6/action/author_attestation","sign_citation":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6/action/citation_signature","submit_replication":"https://pith.science/pith/7IP44RXGUX6ECUQPKYAPHFTJE6/action/replication_record"}},"created_at":"2026-05-18T02:43:08.789154+00:00","updated_at":"2026-05-18T02:43:08.789154+00:00"}