{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:2PFAZHT6SV4TMODHRBZKZLR42L","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":"a86fba4245161b1610f8dee42a5300715ebab1ab3a1d238df9e9ae2ef88f73c3","cross_cats_sorted":["cs.LG","q-fin.CP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-06-06T16:09:57Z","title_canon_sha256":"172a57d4be568b84c456ad20a061f1b78d1f04a4dc7c8552410e596b0e2f9430"},"schema_version":"1.0","source":{"id":"1706.01833","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.01833","created_at":"2026-05-18T00:14:01Z"},{"alias_kind":"arxiv_version","alias_value":"1706.01833v2","created_at":"2026-05-18T00:14:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.01833","created_at":"2026-05-18T00:14:01Z"},{"alias_kind":"pith_short_12","alias_value":"2PFAZHT6SV4T","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2PFAZHT6SV4TMODH","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2PFAZHT6","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:443a8c580f1ee9c85c82114d31d819f658d3c0bccabf936d972aef0275840612","target":"graph","created_at":"2026-05-18T00:14:01Z","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 work, we design a machine learning based method, online adaptive primal support vector regression (SVR), to model the implied volatility surface (IVS). The algorithm proposed is the first derivation and implementation of an online primal kernel SVR. It features enhancements that allow efficient online adaptive learning by embedding the idea of local fitness and budget maintenance to dynamically update support vectors upon pattern drifts. For algorithm acceleration, we implement its most computationally intensive parts in a Field Programmable Gate Arrays hardware, where a 132x speedup o","authors_text":"Diego Klabjan, Yaxiong Zeng","cross_cats":["cs.LG","q-fin.CP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-06-06T16:09:57Z","title":"Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.01833","kind":"arxiv","version":2},"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":"sha256:48b8c48194e61c37d484cbdb92c3ef06c8b0e2dba79abc36f087f6f0aea6cc2e","target":"record","created_at":"2026-05-18T00:14:01Z","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":"a86fba4245161b1610f8dee42a5300715ebab1ab3a1d238df9e9ae2ef88f73c3","cross_cats_sorted":["cs.LG","q-fin.CP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-06-06T16:09:57Z","title_canon_sha256":"172a57d4be568b84c456ad20a061f1b78d1f04a4dc7c8552410e596b0e2f9430"},"schema_version":"1.0","source":{"id":"1706.01833","kind":"arxiv","version":2}},"canonical_sha256":"d3ca0c9e7e95793638678872acae3cd2eb5a7cb9e1981efddc1256e6d70f95f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d3ca0c9e7e95793638678872acae3cd2eb5a7cb9e1981efddc1256e6d70f95f5","first_computed_at":"2026-05-18T00:14:01.078443Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:01.078443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nim1JSS0RO1Ow9/OGlCknfchB+ZuLNoMD3NUL9pa2dlEFbw12FTGEr8XiCm31NrcBplya+nkYDuaaLs7H3ScDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:01.079206Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.01833","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:48b8c48194e61c37d484cbdb92c3ef06c8b0e2dba79abc36f087f6f0aea6cc2e","sha256:443a8c580f1ee9c85c82114d31d819f658d3c0bccabf936d972aef0275840612"],"state_sha256":"1d81f7552f3ccbc241fb309c7c57820d4391f5371b640046f0ffb56658e00ce8"}