{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:VEFEA7GTPPWLYAL3FOG53ZVRDI","short_pith_number":"pith:VEFEA7GT","schema_version":"1.0","canonical_sha256":"a90a407cd37becbc017b2b8ddde6b11a322c1315c769897f284248756b02674b","source":{"kind":"arxiv","id":"1403.6887","version":2},"attestation_state":"computed","paper":{"title":"Distributional Analysis for Model Predictive Deferrable Load Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Adam Wierman, Lingwen Gan, Niangjun Chen, Steven H. Low","submitted_at":"2014-03-26T23:07:09Z","abstract_excerpt":"Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In this paper, we prove strong concentration results on the distribution of the load variance obtained by "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1403.6887","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-03-26T23:07:09Z","cross_cats_sorted":[],"title_canon_sha256":"4c1e5bc96bc99cfe0603221c7158465a78a9577f75812db0ce6cea914e895296","abstract_canon_sha256":"f5df6d0d74e7e8cfccf0df195a0d31adbbce7359035f6018360813b53af56c2d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:42:14.597330Z","signature_b64":"T80H971sgf81J6JKP6N7e5iAJgGPjAp8tg5iYiXu3NOV5Mu6ynJk+14Nm3XxbjlvKpAW1mOKRzX4+1vRZP+NAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a90a407cd37becbc017b2b8ddde6b11a322c1315c769897f284248756b02674b","last_reissued_at":"2026-05-18T02:42:14.596944Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:42:14.596944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Distributional Analysis for Model Predictive Deferrable Load Control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Adam Wierman, Lingwen Gan, Niangjun Chen, Steven H. Low","submitted_at":"2014-03-26T23:07:09Z","abstract_excerpt":"Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In this paper, we prove strong concentration results on the distribution of the load variance obtained by "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.6887","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1403.6887","created_at":"2026-05-18T02:42:14.597000+00:00"},{"alias_kind":"arxiv_version","alias_value":"1403.6887v2","created_at":"2026-05-18T02:42:14.597000+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.6887","created_at":"2026-05-18T02:42:14.597000+00:00"},{"alias_kind":"pith_short_12","alias_value":"VEFEA7GTPPWL","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_16","alias_value":"VEFEA7GTPPWLYAL3","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_8","alias_value":"VEFEA7GT","created_at":"2026-05-18T12:28:52.271510+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI","json":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI.json","graph_json":"https://pith.science/api/pith-number/VEFEA7GTPPWLYAL3FOG53ZVRDI/graph.json","events_json":"https://pith.science/api/pith-number/VEFEA7GTPPWLYAL3FOG53ZVRDI/events.json","paper":"https://pith.science/paper/VEFEA7GT"},"agent_actions":{"view_html":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI","download_json":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI.json","view_paper":"https://pith.science/paper/VEFEA7GT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1403.6887&json=true","fetch_graph":"https://pith.science/api/pith-number/VEFEA7GTPPWLYAL3FOG53ZVRDI/graph.json","fetch_events":"https://pith.science/api/pith-number/VEFEA7GTPPWLYAL3FOG53ZVRDI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI/action/storage_attestation","attest_author":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI/action/author_attestation","sign_citation":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI/action/citation_signature","submit_replication":"https://pith.science/pith/VEFEA7GTPPWLYAL3FOG53ZVRDI/action/replication_record"}},"created_at":"2026-05-18T02:42:14.597000+00:00","updated_at":"2026-05-18T02:42:14.597000+00:00"}