{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5GV4K2RRQPBUXDPGTXTW7EMJRS","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":"6c58c54f14ba518082e84377f4db0fac6ac0dd730b2dd51481abe462e67c3197","cross_cats_sorted":["cs.DS","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-27T15:50:47Z","title_canon_sha256":"49a4368ba844b4e5f7d09c17f46617f0a4b1afbd08bfa9dcea0c9c876243cb45"},"schema_version":"1.0","source":{"id":"2312.16616","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.16616","created_at":"2026-07-05T07:28:32Z"},{"alias_kind":"arxiv_version","alias_value":"2312.16616v1","created_at":"2026-07-05T07:28:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.16616","created_at":"2026-07-05T07:28:32Z"},{"alias_kind":"pith_short_12","alias_value":"5GV4K2RRQPBU","created_at":"2026-07-05T07:28:32Z"},{"alias_kind":"pith_short_16","alias_value":"5GV4K2RRQPBUXDPG","created_at":"2026-07-05T07:28:32Z"},{"alias_kind":"pith_short_8","alias_value":"5GV4K2RR","created_at":"2026-07-05T07:28:32Z"}],"graph_snapshots":[{"event_id":"sha256:21f82e1d1ab18c76e35cf0af637067ad0c14ad92c7d5d9565fc8af64d3b681cd","target":"graph","created_at":"2026-07-05T07:28:32Z","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/2312.16616/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the power of query access for the task of agnostic learning under the Gaussian distribution. In the agnostic model, no assumptions are made on the labels and the goal is to compute a hypothesis that is competitive with the {\\em best-fit} function in a known class, i.e., it achieves error $\\mathrm{opt}+\\epsilon$, where $\\mathrm{opt}$ is the error of the best function in the class. We focus on a general family of Multi-Index Models (MIMs), which are $d$-variate functions that depend only on few relevant directions, i.e., have the form $g(\\mathbf{W} \\mathbf{x})$ for an unknown link funct","authors_text":"Christos Tzamos, Daniel M. Kane, Ilias Diakonikolas, Nikos Zarifis, Vasilis Kontonis","cross_cats":["cs.DS","math.ST","stat.ML","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-27T15:50:47Z","title":"Agnostically Learning Multi-index Models with Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.16616","kind":"arxiv","version":1},"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:eb0e262092e5b3a5dc26dd79bc1d81cdf4504ef1820b65b7fea863499b2f15d3","target":"record","created_at":"2026-07-05T07:28:32Z","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":"6c58c54f14ba518082e84377f4db0fac6ac0dd730b2dd51481abe462e67c3197","cross_cats_sorted":["cs.DS","math.ST","stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-27T15:50:47Z","title_canon_sha256":"49a4368ba844b4e5f7d09c17f46617f0a4b1afbd08bfa9dcea0c9c876243cb45"},"schema_version":"1.0","source":{"id":"2312.16616","kind":"arxiv","version":1}},"canonical_sha256":"e9abc56a3183c34b8de69de76f91898c9d53cb5cc021c86676e192214cda2a17","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9abc56a3183c34b8de69de76f91898c9d53cb5cc021c86676e192214cda2a17","first_computed_at":"2026-07-05T07:28:32.691971Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:28:32.691971Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zG9eNQNMNPpdrHtXYUewZFRrn/DC7gZd89/FbOte8Lqy6sX2Mc6oHGqLm4oc67i3jw4vWbSFE9t5wDLmWJV0Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:28:32.692486Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.16616","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb0e262092e5b3a5dc26dd79bc1d81cdf4504ef1820b65b7fea863499b2f15d3","sha256:21f82e1d1ab18c76e35cf0af637067ad0c14ad92c7d5d9565fc8af64d3b681cd"],"state_sha256":"86b24eba739fbce1a99883410452068d5864eb75c0aa38b59fa7c8ed9afc7849"}