{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:22MZZMWTSPC5ILHXFNQK3BHZRJ","short_pith_number":"pith:22MZZMWT","schema_version":"1.0","canonical_sha256":"d6999cb2d393c5d42cf72b60ad84f98a6b8d65e06ad852ad4b7de3fbe3080652","source":{"kind":"arxiv","id":"1902.00923","version":3},"attestation_state":"computed","paper":{"title":"Finite-Time Error Bounds For Linear Stochastic Approximation and TD Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Lei Ying, R. Srikant","submitted_at":"2019-02-03T16:41:49Z","abstract_excerpt":"We consider the dynamics of a linear stochastic approximation algorithm driven by Markovian noise, and derive finite-time bounds on the moments of the error, i.e., deviation of the output of the algorithm from the equilibrium point of an associated ordinary differential equation (ODE). We obtain finite-time bounds on the mean-square error in the case of constant step-size algorithms by considering the drift of an appropriately chosen Lyapunov function. The Lyapunov function can be interpreted either in terms of Stein's method to obtain bounds on steady-state performance or in terms of Lyapunov"},"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":"1902.00923","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-03T16:41:49Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"94347059bf9036e4d4b5ea409cb9ef71d13b7f5bf4aa39478fc19ae42fcdb943","abstract_canon_sha256":"49fbcfaa37979ccae93f406f4419953c6426f87c156554a5047c58ad80ea00d4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:46.628141Z","signature_b64":"yOF2oeGhs5AuaOOFvHdAjEsS/Txb2tKmTACOykCIiW8M37M2vwdPNV+QjS/6wwuB5O3F2FnanfpT6auPqIVrAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6999cb2d393c5d42cf72b60ad84f98a6b8d65e06ad852ad4b7de3fbe3080652","last_reissued_at":"2026-05-17T23:51:46.627554Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:46.627554Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Finite-Time Error Bounds For Linear Stochastic Approximation and TD Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Lei Ying, R. Srikant","submitted_at":"2019-02-03T16:41:49Z","abstract_excerpt":"We consider the dynamics of a linear stochastic approximation algorithm driven by Markovian noise, and derive finite-time bounds on the moments of the error, i.e., deviation of the output of the algorithm from the equilibrium point of an associated ordinary differential equation (ODE). We obtain finite-time bounds on the mean-square error in the case of constant step-size algorithms by considering the drift of an appropriately chosen Lyapunov function. The Lyapunov function can be interpreted either in terms of Stein's method to obtain bounds on steady-state performance or in terms of Lyapunov"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.00923","kind":"arxiv","version":3},"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":"1902.00923","created_at":"2026-05-17T23:51:46.627647+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.00923v3","created_at":"2026-05-17T23:51:46.627647+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.00923","created_at":"2026-05-17T23:51:46.627647+00:00"},{"alias_kind":"pith_short_12","alias_value":"22MZZMWTSPC5","created_at":"2026-05-18T12:33:07.085635+00:00"},{"alias_kind":"pith_short_16","alias_value":"22MZZMWTSPC5ILHX","created_at":"2026-05-18T12:33:07.085635+00:00"},{"alias_kind":"pith_short_8","alias_value":"22MZZMWT","created_at":"2026-05-18T12:33:07.085635+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/22MZZMWTSPC5ILHXFNQK3BHZRJ","json":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ.json","graph_json":"https://pith.science/api/pith-number/22MZZMWTSPC5ILHXFNQK3BHZRJ/graph.json","events_json":"https://pith.science/api/pith-number/22MZZMWTSPC5ILHXFNQK3BHZRJ/events.json","paper":"https://pith.science/paper/22MZZMWT"},"agent_actions":{"view_html":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ","download_json":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ.json","view_paper":"https://pith.science/paper/22MZZMWT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.00923&json=true","fetch_graph":"https://pith.science/api/pith-number/22MZZMWTSPC5ILHXFNQK3BHZRJ/graph.json","fetch_events":"https://pith.science/api/pith-number/22MZZMWTSPC5ILHXFNQK3BHZRJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ/action/storage_attestation","attest_author":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ/action/author_attestation","sign_citation":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ/action/citation_signature","submit_replication":"https://pith.science/pith/22MZZMWTSPC5ILHXFNQK3BHZRJ/action/replication_record"}},"created_at":"2026-05-17T23:51:46.627647+00:00","updated_at":"2026-05-17T23:51:46.627647+00:00"}