{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:ZNCYL2XTYXRTXONCH3H3BCMHV6","short_pith_number":"pith:ZNCYL2XT","schema_version":"1.0","canonical_sha256":"cb4585eaf3c5e33bb9a23ecfb08987afb4a9d5d8d2579df3e42bf814ab5f3c81","source":{"kind":"arxiv","id":"1403.5591","version":1},"attestation_state":"computed","paper":{"title":"Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Angelia Nedic, Farzad Yousefian, Uday V. Shanbhag","submitted_at":"2014-03-21T23:27:10Z","abstract_excerpt":"We consider stochastic variational inequality problems where the mapping is monotone over a compact convex set. We present two robust variants of stochastic extragradient algorithms for solving such problems. Of these, the first scheme employs an iterative averaging technique where we consider a generalized choice for the weights in the averaged sequence. Our first contribution is to show that using an appropriate choice for these weights, a suitably defined gap function attains the optimal rate of convergence ${\\cal O}\\left(\\frac{1}{\\sqrt{k}}\\right)$. In the second part of the paper, under an"},"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":"1403.5591","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2014-03-21T23:27:10Z","cross_cats_sorted":[],"title_canon_sha256":"703ea3c49abedcdf2b69cd5fbf9cfc692b2873e812cc0d43cf78398f10327dca","abstract_canon_sha256":"2171e54e25ed1d16a7961745f59205d0a3cdd84807fea60775237e73ff574a65"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:55:49.441146Z","signature_b64":"+rL6R2Me49ZwTQFLQDGIdEGDvyOyQaklayCRiTbWB3PTnIR9JCdnAgFNgaW9RXWnOoH/vFeknvWtuuCVaeFhCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cb4585eaf3c5e33bb9a23ecfb08987afb4a9d5d8d2579df3e42bf814ab5f3c81","last_reissued_at":"2026-05-18T02:55:49.440561Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:55:49.440561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Angelia Nedic, Farzad Yousefian, Uday V. Shanbhag","submitted_at":"2014-03-21T23:27:10Z","abstract_excerpt":"We consider stochastic variational inequality problems where the mapping is monotone over a compact convex set. We present two robust variants of stochastic extragradient algorithms for solving such problems. Of these, the first scheme employs an iterative averaging technique where we consider a generalized choice for the weights in the averaged sequence. Our first contribution is to show that using an appropriate choice for these weights, a suitably defined gap function attains the optimal rate of convergence ${\\cal O}\\left(\\frac{1}{\\sqrt{k}}\\right)$. In the second part of the paper, under an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1403.5591","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1403.5591","created_at":"2026-05-18T02:55:49.440642+00:00"},{"alias_kind":"arxiv_version","alias_value":"1403.5591v1","created_at":"2026-05-18T02:55:49.440642+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1403.5591","created_at":"2026-05-18T02:55:49.440642+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZNCYL2XTYXRT","created_at":"2026-05-18T12:28:59.999130+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZNCYL2XTYXRTXONC","created_at":"2026-05-18T12:28:59.999130+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZNCYL2XT","created_at":"2026-05-18T12:28:59.999130+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/ZNCYL2XTYXRTXONCH3H3BCMHV6","json":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6.json","graph_json":"https://pith.science/api/pith-number/ZNCYL2XTYXRTXONCH3H3BCMHV6/graph.json","events_json":"https://pith.science/api/pith-number/ZNCYL2XTYXRTXONCH3H3BCMHV6/events.json","paper":"https://pith.science/paper/ZNCYL2XT"},"agent_actions":{"view_html":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6","download_json":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6.json","view_paper":"https://pith.science/paper/ZNCYL2XT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1403.5591&json=true","fetch_graph":"https://pith.science/api/pith-number/ZNCYL2XTYXRTXONCH3H3BCMHV6/graph.json","fetch_events":"https://pith.science/api/pith-number/ZNCYL2XTYXRTXONCH3H3BCMHV6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6/action/storage_attestation","attest_author":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6/action/author_attestation","sign_citation":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6/action/citation_signature","submit_replication":"https://pith.science/pith/ZNCYL2XTYXRTXONCH3H3BCMHV6/action/replication_record"}},"created_at":"2026-05-18T02:55:49.440642+00:00","updated_at":"2026-05-18T02:55:49.440642+00:00"}