{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:YLPKCG37VJQMR4JLFNZZERU6I3","short_pith_number":"pith:YLPKCG37","canonical_record":{"source":{"id":"1811.07186","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-11-17T16:48:24Z","cross_cats_sorted":[],"title_canon_sha256":"d19cbb2e0a87e16af22a5bb84814dff8da559c26a71e295d59f8199354dc944f","abstract_canon_sha256":"de92e4d90a09fd9ff3659fa1a9753cdf751ed9595d368c75eb55325e5afa855f"},"schema_version":"1.0"},"canonical_sha256":"c2dea11b7faa60c8f12b2b7392469e46ea100e9874c804376f2df5f265e2ebe9","source":{"kind":"arxiv","id":"1811.07186","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.07186","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"arxiv_version","alias_value":"1811.07186v1","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07186","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"pith_short_12","alias_value":"YLPKCG37VJQM","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YLPKCG37VJQMR4JL","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YLPKCG37","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:YLPKCG37VJQMR4JLFNZZERU6I3","target":"record","payload":{"canonical_record":{"source":{"id":"1811.07186","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-11-17T16:48:24Z","cross_cats_sorted":[],"title_canon_sha256":"d19cbb2e0a87e16af22a5bb84814dff8da559c26a71e295d59f8199354dc944f","abstract_canon_sha256":"de92e4d90a09fd9ff3659fa1a9753cdf751ed9595d368c75eb55325e5afa855f"},"schema_version":"1.0"},"canonical_sha256":"c2dea11b7faa60c8f12b2b7392469e46ea100e9874c804376f2df5f265e2ebe9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:28.676100Z","signature_b64":"Zo6Yzz8lUMgmMCTxjBk4E5E0nASXF3BmvkMqwKL1xvvIaIPa4LHHz9IooOM/BVk/sjP7Y/6Q7sXpuk6wOTZnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2dea11b7faa60c8f12b2b7392469e46ea100e9874c804376f2df5f265e2ebe9","last_reissued_at":"2026-05-18T00:00:28.675387Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:28.675387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.07186","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":"2026-05-18T00:00:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W2DNRhtkU24R/kINOdAS4Uiy2BrAo4aOd0U3P/ai9uoeZvUUsuBmpDGvrOhk01L0NLm7XS+VO/8XipbZ192pCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T05:44:26.644199Z"},"content_sha256":"673c0a35a95d28a1776547cb9a520c4dce0568f1b5697bd57c41deb4752b5949","schema_version":"1.0","event_id":"sha256:673c0a35a95d28a1776547cb9a520c4dce0568f1b5697bd57c41deb4752b5949"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:YLPKCG37VJQMR4JLFNZZERU6I3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Allocations for Sample Average Approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.CO","authors_text":"Harsha Honnappa, Prateek Jaiswal, Raghu Pasupathy","submitted_at":"2018-11-17T16:48:24Z","abstract_excerpt":"We consider a single stage stochastic program without recourse with a strictly convex loss function. We assume a compact decision space and grid it with a finite set of points. In addition, we assume that the decision maker can generate samples of the stochastic variable independently at each grid point and form a sample average approximation (SAA) of the stochastic program. Our objective in this paper is to characterize an asymptotically optimal linear sample allocation rule, given a fixed sampling budget, which maximizes the decay rate of probability of making false decision."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07186","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":"2026-05-18T00:00:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BTPyCPgsSmutR0RxBnehd7E+aWjJfbWFoC/lXK2FffEM0lHjetuLbQ7ascasyVi4Q87lfPl/XQGzrO8j+Ac/Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T05:44:26.644566Z"},"content_sha256":"191266fc5d07b6fb7a8a6e34fbf8bb224720081c24e48d024ca91ccba9f61776","schema_version":"1.0","event_id":"sha256:191266fc5d07b6fb7a8a6e34fbf8bb224720081c24e48d024ca91ccba9f61776"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YLPKCG37VJQMR4JLFNZZERU6I3/bundle.json","state_url":"https://pith.science/pith/YLPKCG37VJQMR4JLFNZZERU6I3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YLPKCG37VJQMR4JLFNZZERU6I3/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":"2026-06-02T05:44:26Z","links":{"resolver":"https://pith.science/pith/YLPKCG37VJQMR4JLFNZZERU6I3","bundle":"https://pith.science/pith/YLPKCG37VJQMR4JLFNZZERU6I3/bundle.json","state":"https://pith.science/pith/YLPKCG37VJQMR4JLFNZZERU6I3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YLPKCG37VJQMR4JLFNZZERU6I3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:YLPKCG37VJQMR4JLFNZZERU6I3","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":"de92e4d90a09fd9ff3659fa1a9753cdf751ed9595d368c75eb55325e5afa855f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-11-17T16:48:24Z","title_canon_sha256":"d19cbb2e0a87e16af22a5bb84814dff8da559c26a71e295d59f8199354dc944f"},"schema_version":"1.0","source":{"id":"1811.07186","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.07186","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"arxiv_version","alias_value":"1811.07186v1","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.07186","created_at":"2026-05-18T00:00:28Z"},{"alias_kind":"pith_short_12","alias_value":"YLPKCG37VJQM","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YLPKCG37VJQMR4JL","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YLPKCG37","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:191266fc5d07b6fb7a8a6e34fbf8bb224720081c24e48d024ca91ccba9f61776","target":"graph","created_at":"2026-05-18T00:00:28Z","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":"We consider a single stage stochastic program without recourse with a strictly convex loss function. We assume a compact decision space and grid it with a finite set of points. In addition, we assume that the decision maker can generate samples of the stochastic variable independently at each grid point and form a sample average approximation (SAA) of the stochastic program. Our objective in this paper is to characterize an asymptotically optimal linear sample allocation rule, given a fixed sampling budget, which maximizes the decay rate of probability of making false decision.","authors_text":"Harsha Honnappa, Prateek Jaiswal, Raghu Pasupathy","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-11-17T16:48:24Z","title":"Optimal Allocations for Sample Average Approximation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.07186","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":"sha256:673c0a35a95d28a1776547cb9a520c4dce0568f1b5697bd57c41deb4752b5949","target":"record","created_at":"2026-05-18T00:00:28Z","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":"de92e4d90a09fd9ff3659fa1a9753cdf751ed9595d368c75eb55325e5afa855f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.CO","submitted_at":"2018-11-17T16:48:24Z","title_canon_sha256":"d19cbb2e0a87e16af22a5bb84814dff8da559c26a71e295d59f8199354dc944f"},"schema_version":"1.0","source":{"id":"1811.07186","kind":"arxiv","version":1}},"canonical_sha256":"c2dea11b7faa60c8f12b2b7392469e46ea100e9874c804376f2df5f265e2ebe9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2dea11b7faa60c8f12b2b7392469e46ea100e9874c804376f2df5f265e2ebe9","first_computed_at":"2026-05-18T00:00:28.675387Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:28.675387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Zo6Yzz8lUMgmMCTxjBk4E5E0nASXF3BmvkMqwKL1xvvIaIPa4LHHz9IooOM/BVk/sjP7Y/6Q7sXpuk6wOTZnAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:28.676100Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.07186","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:673c0a35a95d28a1776547cb9a520c4dce0568f1b5697bd57c41deb4752b5949","sha256:191266fc5d07b6fb7a8a6e34fbf8bb224720081c24e48d024ca91ccba9f61776"],"state_sha256":"f2956c6e7cbfb6d8706163dc31abd60a9df0d64c1ef8c4c039e0a58d96a116f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BZ8LCFFum7oFhpXTypA71iDtWbxLb65TJ2XBKj2ffFfR2t/Y15dd4Ui9dql6kmXzTwqPbRS6AWnZbpSoO52dCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T05:44:26.646571Z","bundle_sha256":"ddc91f60bccf60c1e96bc2d407b4db6366415b04569d0b974d6cde02c7565cdd"}}