{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OW6B6RUPKX3FGNS3V4LUN7SIML","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":"8434ad325fda7e6f09d8cc88b2282baa08c1f2616302e7b87a93d826d95508b0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-25T21:57:35Z","title_canon_sha256":"70837e6b734b2b511d19e4583e1868305df5a7a9ab9b44b835367289246c7db2"},"schema_version":"1.0","source":{"id":"2503.20087","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.20087","created_at":"2026-07-05T10:43:06Z"},{"alias_kind":"arxiv_version","alias_value":"2503.20087v2","created_at":"2026-07-05T10:43:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.20087","created_at":"2026-07-05T10:43:06Z"},{"alias_kind":"pith_short_12","alias_value":"OW6B6RUPKX3F","created_at":"2026-07-05T10:43:06Z"},{"alias_kind":"pith_short_16","alias_value":"OW6B6RUPKX3FGNS3","created_at":"2026-07-05T10:43:06Z"},{"alias_kind":"pith_short_8","alias_value":"OW6B6RUP","created_at":"2026-07-05T10:43:06Z"}],"graph_snapshots":[{"event_id":"sha256:59d496d51b9e221db11561c195059fb48b9c38bd4442607bf52e816ecf16b26a","target":"graph","created_at":"2026-07-05T10:43:06Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.20087/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce a novel multi-kernel learning algorithm, VAW$^2$, for online least squares regression in reproducing kernel Hilbert spaces (RKHS). VAW$^2$ leverages random Fourier feature-based functional approximation and the Vovk-Azoury-Warmuth (VAW) method in a two-level procedure: VAW is used to construct expert strategies from random features generated for each kernel at the first level, and then again to combine their predictions at the second level. A theoretical analysis yields a regret bound of $O(T^{1/2}\\ln T)$ in expectation with respect to artificial randomness, when the number of ran","authors_text":"Dmitry B. Rokhlin, Olga V. Gurtovaya","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-25T21:57:35Z","title":"Random feature-based double Vovk-Azoury-Warmuth algorithm for online multi-kernel learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.20087","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":"sha256:898a315d14b3884cab040bf66535f2b2f413803b4a087993afd1c3180a8ae034","target":"record","created_at":"2026-07-05T10:43:06Z","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":"8434ad325fda7e6f09d8cc88b2282baa08c1f2616302e7b87a93d826d95508b0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-25T21:57:35Z","title_canon_sha256":"70837e6b734b2b511d19e4583e1868305df5a7a9ab9b44b835367289246c7db2"},"schema_version":"1.0","source":{"id":"2503.20087","kind":"arxiv","version":2}},"canonical_sha256":"75bc1f468f55f653365baf1746fe4862ec253e939c6e7e35aa26b4e51855f099","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75bc1f468f55f653365baf1746fe4862ec253e939c6e7e35aa26b4e51855f099","first_computed_at":"2026-07-05T10:43:06.482014Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:43:06.482014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XkasvBzV1CN4k2qF4lJfMjTEzRyOG+JByfkortvdMfwjWrLQqkzdapTEJ4VLWN/MvHVQbTqCF16rR2HX4mG3BA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:43:06.482526Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.20087","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:898a315d14b3884cab040bf66535f2b2f413803b4a087993afd1c3180a8ae034","sha256:59d496d51b9e221db11561c195059fb48b9c38bd4442607bf52e816ecf16b26a"],"state_sha256":"b36f9007efabde05c4ceb1b95b7fc400993846bff2e0a4a50f9d37f7a84b9e38"}