{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:D2PAWJJ6HK6OLFLAVR4MNC5CN4","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":"2ec6181c607fc32f05cdc158301496c008002d1d7f01d3e71b3b4012aa2f22cb","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-23T04:05:25Z","title_canon_sha256":"3d798d5199346110d7c0e2aca9d5dca92e9a45c7e0579a1e27d8237f85e22145"},"schema_version":"1.0","source":{"id":"1908.08656","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.08656","created_at":"2026-07-05T01:34:49Z"},{"alias_kind":"arxiv_version","alias_value":"1908.08656v2","created_at":"2026-07-05T01:34:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.08656","created_at":"2026-07-05T01:34:49Z"},{"alias_kind":"pith_short_12","alias_value":"D2PAWJJ6HK6O","created_at":"2026-07-05T01:34:49Z"},{"alias_kind":"pith_short_16","alias_value":"D2PAWJJ6HK6OLFLA","created_at":"2026-07-05T01:34:49Z"},{"alias_kind":"pith_short_8","alias_value":"D2PAWJJ6","created_at":"2026-07-05T01:34:49Z"}],"graph_snapshots":[{"event_id":"sha256:b8595f5cb9ac1eb8c8ec37bb733f257193df8551d9cc73c4fdabdc3f6c54ae19","target":"graph","created_at":"2026-07-05T01:34:49Z","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/1908.08656/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Top-k maximum inner product search (MIPS) is a central task in many machine learning applications. This paper extends top-k MIPS with a budgeted setting, that asks for the best approximate top-k MIPS given a limit of B computational operations. We investigate recent advanced sampling algorithms, including wedge and diamond sampling to solve it. Though the design of these sampling schemes naturally supports budgeted top-k MIPS, they suffer from the linear cost from scanning all data points to retrieve top-k results and the performance degradation for handling negative inputs.\n  This paper makes","authors_text":"Ninh Pham, Stephan S. Lorenzen","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-23T04:05:25Z","title":"Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.08656","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":"sha256:2f554f14fa8fd004e11c3bc3c68f08e65a2a45d0d5af31591df5b15529c28fad","target":"record","created_at":"2026-07-05T01:34:49Z","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":"2ec6181c607fc32f05cdc158301496c008002d1d7f01d3e71b3b4012aa2f22cb","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2019-08-23T04:05:25Z","title_canon_sha256":"3d798d5199346110d7c0e2aca9d5dca92e9a45c7e0579a1e27d8237f85e22145"},"schema_version":"1.0","source":{"id":"1908.08656","kind":"arxiv","version":2}},"canonical_sha256":"1e9e0b253e3abce59560ac78c68ba26f265edccc97a336d1c783c0cd023c7718","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e9e0b253e3abce59560ac78c68ba26f265edccc97a336d1c783c0cd023c7718","first_computed_at":"2026-07-05T01:34:49.431361Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:34:49.431361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vfSfRVh8o0x71sAfbvj0GwDhONT4hKssOWGbc7hCLRFQvwoUCMOMEp+BOBk7pbzob8NLJYfdHY691pu25xzwDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:34:49.431715Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.08656","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f554f14fa8fd004e11c3bc3c68f08e65a2a45d0d5af31591df5b15529c28fad","sha256:b8595f5cb9ac1eb8c8ec37bb733f257193df8551d9cc73c4fdabdc3f6c54ae19"],"state_sha256":"4bd31db7678caa09b0982af54cea21df8e019f23d6337c67d53e5de0dfe3c346"}