{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:O77M76L57BQC4P2JYJAFU6DWFJ","short_pith_number":"pith:O77M76L5","canonical_record":{"source":{"id":"1906.04133","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-10T17:10:51Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"40d214209841b67c2dc23f7d38abdd8a043480624e3b092fdb6d22cf043e8125","abstract_canon_sha256":"67a4b6c83d6c3a7133cc5bca2aeae4015c46d01d66be0ef313f52795478eb9d7"},"schema_version":"1.0"},"canonical_sha256":"77fecff97df8602e3f49c2405a78762a73a4877cb1182aa327ec47e5fa16dc57","source":{"kind":"arxiv","id":"1906.04133","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.04133","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"arxiv_version","alias_value":"1906.04133v1","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.04133","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"pith_short_12","alias_value":"O77M76L57BQC","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"O77M76L57BQC4P2J","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"O77M76L5","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:O77M76L57BQC4P2JYJAFU6DWFJ","target":"record","payload":{"canonical_record":{"source":{"id":"1906.04133","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-10T17:10:51Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"40d214209841b67c2dc23f7d38abdd8a043480624e3b092fdb6d22cf043e8125","abstract_canon_sha256":"67a4b6c83d6c3a7133cc5bca2aeae4015c46d01d66be0ef313f52795478eb9d7"},"schema_version":"1.0"},"canonical_sha256":"77fecff97df8602e3f49c2405a78762a73a4877cb1182aa327ec47e5fa16dc57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:43.798025Z","signature_b64":"VuQfqSDdw3tZvZdzNFck/nf2aalk8I+uktGobvwAf+Th+1hbiBm86B4Kyv22YXMPvvwOEzY8Ug3LhSk+gOAKAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"77fecff97df8602e3f49c2405a78762a73a4877cb1182aa327ec47e5fa16dc57","last_reissued_at":"2026-05-17T23:43:43.797288Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:43.797288Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.04133","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:43:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2uXmA9ivvwf3QOMwuZo+Tqp97H61nJS+3eN55LzEk4vPeTh52AXicv34r5WMrbG+OVKLkKc3Ayko6Qi6vlXRCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:18:46.065400Z"},"content_sha256":"3cb7ba57e735845b842ce86976b6466a58b49831fbe661981232ae0cf2caa440","schema_version":"1.0","event_id":"sha256:3cb7ba57e735845b842ce86976b6466a58b49831fbe661981232ae0cf2caa440"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:O77M76L57BQC4P2JYJAFU6DWFJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bayesian experimental design using regularized determinantal point processes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Feynman Liang, Michael W. Mahoney, Micha{\\l} Derezi\\'nski","submitted_at":"2019-06-10T17:10:51Z","abstract_excerpt":"In experimental design, we are given $n$ vectors in $d$ dimensions, and our goal is to select $k\\ll n$ of them to perform expensive measurements, e.g., to obtain labels/responses, for a linear regression task. Many statistical criteria have been proposed for choosing the optimal design, with popular choices including A- and D-optimality. If prior knowledge is given, typically in the form of a $d\\times d$ precision matrix $\\mathbf A$, then all of the criteria can be extended to incorporate that information via a Bayesian framework. In this paper, we demonstrate a new fundamental connection betw"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.04133","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:43:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R3lNpjWZfMfgcyFDrH6WFsTqTn1Fr9tpcw3DYhtuh5sdHgmTqPihdoQniu7Aw62T3UY1b/uzIRh5hQQEQKhDAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T16:18:46.066068Z"},"content_sha256":"5cd66a079f5cf73f89524193af0a301910109b767f6ccc29be62a4367ddbd9f2","schema_version":"1.0","event_id":"sha256:5cd66a079f5cf73f89524193af0a301910109b767f6ccc29be62a4367ddbd9f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/O77M76L57BQC4P2JYJAFU6DWFJ/bundle.json","state_url":"https://pith.science/pith/O77M76L57BQC4P2JYJAFU6DWFJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/O77M76L57BQC4P2JYJAFU6DWFJ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-07T16:18:46Z","links":{"resolver":"https://pith.science/pith/O77M76L57BQC4P2JYJAFU6DWFJ","bundle":"https://pith.science/pith/O77M76L57BQC4P2JYJAFU6DWFJ/bundle.json","state":"https://pith.science/pith/O77M76L57BQC4P2JYJAFU6DWFJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/O77M76L57BQC4P2JYJAFU6DWFJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:O77M76L57BQC4P2JYJAFU6DWFJ","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":"67a4b6c83d6c3a7133cc5bca2aeae4015c46d01d66be0ef313f52795478eb9d7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-10T17:10:51Z","title_canon_sha256":"40d214209841b67c2dc23f7d38abdd8a043480624e3b092fdb6d22cf043e8125"},"schema_version":"1.0","source":{"id":"1906.04133","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.04133","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"arxiv_version","alias_value":"1906.04133v1","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.04133","created_at":"2026-05-17T23:43:43Z"},{"alias_kind":"pith_short_12","alias_value":"O77M76L57BQC","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"O77M76L57BQC4P2J","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"O77M76L5","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:5cd66a079f5cf73f89524193af0a301910109b767f6ccc29be62a4367ddbd9f2","target":"graph","created_at":"2026-05-17T23:43:43Z","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 experimental design, we are given $n$ vectors in $d$ dimensions, and our goal is to select $k\\ll n$ of them to perform expensive measurements, e.g., to obtain labels/responses, for a linear regression task. Many statistical criteria have been proposed for choosing the optimal design, with popular choices including A- and D-optimality. If prior knowledge is given, typically in the form of a $d\\times d$ precision matrix $\\mathbf A$, then all of the criteria can be extended to incorporate that information via a Bayesian framework. In this paper, we demonstrate a new fundamental connection betw","authors_text":"Feynman Liang, Michael W. Mahoney, Micha{\\l} Derezi\\'nski","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-10T17:10:51Z","title":"Bayesian experimental design using regularized determinantal point processes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.04133","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":"sha256:3cb7ba57e735845b842ce86976b6466a58b49831fbe661981232ae0cf2caa440","target":"record","created_at":"2026-05-17T23:43:43Z","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":"67a4b6c83d6c3a7133cc5bca2aeae4015c46d01d66be0ef313f52795478eb9d7","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-10T17:10:51Z","title_canon_sha256":"40d214209841b67c2dc23f7d38abdd8a043480624e3b092fdb6d22cf043e8125"},"schema_version":"1.0","source":{"id":"1906.04133","kind":"arxiv","version":1}},"canonical_sha256":"77fecff97df8602e3f49c2405a78762a73a4877cb1182aa327ec47e5fa16dc57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"77fecff97df8602e3f49c2405a78762a73a4877cb1182aa327ec47e5fa16dc57","first_computed_at":"2026-05-17T23:43:43.797288Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:43:43.797288Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VuQfqSDdw3tZvZdzNFck/nf2aalk8I+uktGobvwAf+Th+1hbiBm86B4Kyv22YXMPvvwOEzY8Ug3LhSk+gOAKAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:43:43.798025Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.04133","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3cb7ba57e735845b842ce86976b6466a58b49831fbe661981232ae0cf2caa440","sha256:5cd66a079f5cf73f89524193af0a301910109b767f6ccc29be62a4367ddbd9f2"],"state_sha256":"26554d1890d7fd1914ba399644cda91bda7904c36a62174168d15c7321bce49b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"brS+HiUqb/S2ZCQaoYl9vSxNBhvB6FITAaXs3956Rx5+A62bQczpD20af4P67dmX6tSyTDaNxg1ygsY8sF9tDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T16:18:46.069698Z","bundle_sha256":"21d305ac261877d0cc3e698e2b9fef7180f035d6fc36049c5d63778dfb69769b"}}