{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:ZZSCPM2S6L73YAEF6MZHLDOWSC","short_pith_number":"pith:ZZSCPM2S","schema_version":"1.0","canonical_sha256":"ce6427b352f2ffbc0085f332758dd6909b7782b3c4e7724df89b3f13db4e17e6","source":{"kind":"arxiv","id":"1707.03191","version":1},"attestation_state":"computed","paper":{"title":"Towards an automated method based on Iterated Local Search optimization for tuning the parameters of Support Vector Machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Dimitrios Mavroeidis, Jacek Kustra, Monique Hendriks, Pieter Vos, Sergio Consoli","submitted_at":"2017-07-11T09:29:58Z","abstract_excerpt":"We provide preliminary details and formulation of an optimization strategy under current development that is able to automatically tune the parameters of a Support Vector Machine over new datasets. The optimization strategy is a heuristic based on Iterated Local Search, a modification of classic hill climbing which iterates calls to a local search routine."},"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":"1707.03191","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-07-11T09:29:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7e75fba308037011be604d9aacc20b5dc574d30f73ecf755e3e0abea959ed481","abstract_canon_sha256":"c5290d9ec798d0e3c4732938eda4e9c607ab5678baaa14bd9d594397f6dd9459"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:29.634598Z","signature_b64":"KwJv7Fmm+3Iar/d83OHjIFn48DB57nGIrBcrRonbN8Ez9aqQFMHvmKtWHZruxKIuuj6wi0hXldehw3+Mlgb4Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce6427b352f2ffbc0085f332758dd6909b7782b3c4e7724df89b3f13db4e17e6","last_reissued_at":"2026-05-18T00:40:29.633971Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:29.633971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards an automated method based on Iterated Local Search optimization for tuning the parameters of Support Vector Machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Dimitrios Mavroeidis, Jacek Kustra, Monique Hendriks, Pieter Vos, Sergio Consoli","submitted_at":"2017-07-11T09:29:58Z","abstract_excerpt":"We provide preliminary details and formulation of an optimization strategy under current development that is able to automatically tune the parameters of a Support Vector Machine over new datasets. The optimization strategy is a heuristic based on Iterated Local Search, a modification of classic hill climbing which iterates calls to a local search routine."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.03191","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":"1707.03191","created_at":"2026-05-18T00:40:29.634073+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.03191v1","created_at":"2026-05-18T00:40:29.634073+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.03191","created_at":"2026-05-18T00:40:29.634073+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZZSCPM2S6L73","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZZSCPM2S6L73YAEF","created_at":"2026-05-18T12:31:59.375834+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZZSCPM2S","created_at":"2026-05-18T12:31:59.375834+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/ZZSCPM2S6L73YAEF6MZHLDOWSC","json":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC.json","graph_json":"https://pith.science/api/pith-number/ZZSCPM2S6L73YAEF6MZHLDOWSC/graph.json","events_json":"https://pith.science/api/pith-number/ZZSCPM2S6L73YAEF6MZHLDOWSC/events.json","paper":"https://pith.science/paper/ZZSCPM2S"},"agent_actions":{"view_html":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC","download_json":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC.json","view_paper":"https://pith.science/paper/ZZSCPM2S","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.03191&json=true","fetch_graph":"https://pith.science/api/pith-number/ZZSCPM2S6L73YAEF6MZHLDOWSC/graph.json","fetch_events":"https://pith.science/api/pith-number/ZZSCPM2S6L73YAEF6MZHLDOWSC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC/action/storage_attestation","attest_author":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC/action/author_attestation","sign_citation":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC/action/citation_signature","submit_replication":"https://pith.science/pith/ZZSCPM2S6L73YAEF6MZHLDOWSC/action/replication_record"}},"created_at":"2026-05-18T00:40:29.634073+00:00","updated_at":"2026-05-18T00:40:29.634073+00:00"}