{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:FXTPUIPKS4BAG6LEKMF5DRGEN5","short_pith_number":"pith:FXTPUIPK","canonical_record":{"source":{"id":"1809.06277","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T15:32:20Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"350f09afcbb6782bcbbd0ce7159751994b8a0d08521ccb7e27cdce233e1e5f5d","abstract_canon_sha256":"08bf327e503d9cb73bc18283337eb33cfc972b69a0dfa05960b2a8f3836f2262"},"schema_version":"1.0"},"canonical_sha256":"2de6fa21ea9702037964530bd1c4c46f4bd9c2ef04b486342d41cde35c03a1ea","source":{"kind":"arxiv","id":"1809.06277","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06277","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06277v2","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06277","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"pith_short_12","alias_value":"FXTPUIPKS4BA","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"FXTPUIPKS4BAG6LE","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"FXTPUIPK","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:FXTPUIPKS4BAG6LEKMF5DRGEN5","target":"record","payload":{"canonical_record":{"source":{"id":"1809.06277","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T15:32:20Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"350f09afcbb6782bcbbd0ce7159751994b8a0d08521ccb7e27cdce233e1e5f5d","abstract_canon_sha256":"08bf327e503d9cb73bc18283337eb33cfc972b69a0dfa05960b2a8f3836f2262"},"schema_version":"1.0"},"canonical_sha256":"2de6fa21ea9702037964530bd1c4c46f4bd9c2ef04b486342d41cde35c03a1ea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:39.235190Z","signature_b64":"0OHdLFHlSAFzDQVuUtXMLkD+YNT3z4A2zcMTCVS9bhJbe5cT/pnrUjvmU/9dz28lKd4PuGRvpGbBUyergPQSAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2de6fa21ea9702037964530bd1c4c46f4bd9c2ef04b486342d41cde35c03a1ea","last_reissued_at":"2026-05-17T23:54:39.234605Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:39.234605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.06277","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kvP1hhinKuIMTYM532BA4qO57GrFNRcZq1YO+mH1E2jnOe9H/yPblSlvgQH+j1kgG63MNG0O+fJ3lWJis4J/Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T00:49:48.821494Z"},"content_sha256":"640b864e16471446bdf643ff2a2e2c350ebb1982b2c0ab53fb310e136234d21f","schema_version":"1.0","event_id":"sha256:640b864e16471446bdf643ff2a2e2c350ebb1982b2c0ab53fb310e136234d21f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:FXTPUIPKS4BAG6LEKMF5DRGEN5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Matrix Momentum Stochastic Approximation and Applications to Q-learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY"],"primary_cat":"math.OC","authors_text":"Adithya M. Devraj, Ana Bu\\v{s}i\\'c, Sean Meyn","submitted_at":"2018-09-17T15:32:20Z","abstract_excerpt":"Acceleration is an increasingly common theme in the stochastic optimization literature. The two most common examples are Nesterov's method, and Polyak's momentum technique. In this paper two new algorithms are introduced for root finding problems: 1) PolSA is a root finding algorithm with specially designed matrix momentum, and 2) NeSA can be regarded as a variant of Nesterov's algorithm, or a simplification of PolSA. The PolSA algorithm is new even in the context of optimization (when cast as a root finding problem).\n  The research surveyed in this paper is motivated by applications to reinfo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06277","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:54:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fUoF4BdDwYlkLigipzAFAeLaHTZizbgqIdw6z36BjgulCshZcFkiDMj0fZ3NFIkOuskLLbacjB229SgMvD0TCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T00:49:48.821839Z"},"content_sha256":"b7f4d017353def5d36ddf1a8af276fe62f7b97f83684531f48e26ee33239e12c","schema_version":"1.0","event_id":"sha256:b7f4d017353def5d36ddf1a8af276fe62f7b97f83684531f48e26ee33239e12c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/bundle.json","state_url":"https://pith.science/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/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":"2026-06-26T00:49:48Z","links":{"resolver":"https://pith.science/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5","bundle":"https://pith.science/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/bundle.json","state":"https://pith.science/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FXTPUIPKS4BAG6LEKMF5DRGEN5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:FXTPUIPKS4BAG6LEKMF5DRGEN5","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":"08bf327e503d9cb73bc18283337eb33cfc972b69a0dfa05960b2a8f3836f2262","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T15:32:20Z","title_canon_sha256":"350f09afcbb6782bcbbd0ce7159751994b8a0d08521ccb7e27cdce233e1e5f5d"},"schema_version":"1.0","source":{"id":"1809.06277","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06277","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06277v2","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06277","created_at":"2026-05-17T23:54:39Z"},{"alias_kind":"pith_short_12","alias_value":"FXTPUIPKS4BA","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"FXTPUIPKS4BAG6LE","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"FXTPUIPK","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:b7f4d017353def5d36ddf1a8af276fe62f7b97f83684531f48e26ee33239e12c","target":"graph","created_at":"2026-05-17T23:54:39Z","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":"Acceleration is an increasingly common theme in the stochastic optimization literature. The two most common examples are Nesterov's method, and Polyak's momentum technique. In this paper two new algorithms are introduced for root finding problems: 1) PolSA is a root finding algorithm with specially designed matrix momentum, and 2) NeSA can be regarded as a variant of Nesterov's algorithm, or a simplification of PolSA. The PolSA algorithm is new even in the context of optimization (when cast as a root finding problem).\n  The research surveyed in this paper is motivated by applications to reinfo","authors_text":"Adithya M. Devraj, Ana Bu\\v{s}i\\'c, Sean Meyn","cross_cats":["cs.LG","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T15:32:20Z","title":"Optimal Matrix Momentum Stochastic Approximation and Applications to Q-learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06277","kind":"arxiv","version":2},"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":"sha256:640b864e16471446bdf643ff2a2e2c350ebb1982b2c0ab53fb310e136234d21f","target":"record","created_at":"2026-05-17T23:54:39Z","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":"08bf327e503d9cb73bc18283337eb33cfc972b69a0dfa05960b2a8f3836f2262","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2018-09-17T15:32:20Z","title_canon_sha256":"350f09afcbb6782bcbbd0ce7159751994b8a0d08521ccb7e27cdce233e1e5f5d"},"schema_version":"1.0","source":{"id":"1809.06277","kind":"arxiv","version":2}},"canonical_sha256":"2de6fa21ea9702037964530bd1c4c46f4bd9c2ef04b486342d41cde35c03a1ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2de6fa21ea9702037964530bd1c4c46f4bd9c2ef04b486342d41cde35c03a1ea","first_computed_at":"2026-05-17T23:54:39.234605Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:39.234605Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0OHdLFHlSAFzDQVuUtXMLkD+YNT3z4A2zcMTCVS9bhJbe5cT/pnrUjvmU/9dz28lKd4PuGRvpGbBUyergPQSAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:39.235190Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.06277","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:640b864e16471446bdf643ff2a2e2c350ebb1982b2c0ab53fb310e136234d21f","sha256:b7f4d017353def5d36ddf1a8af276fe62f7b97f83684531f48e26ee33239e12c"],"state_sha256":"8d25ae14553718e169197e8655bc8b3470c6703103ad0bf05e4b99cd212c916b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0bxDcGY25A6EiFDENIuJezxWveoM7PykLEq2bhlNNe3/ot+TWnH7eKtVUjUaH16XZcZxzM7jUDCawoiCA7sFDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T00:49:48.823789Z","bundle_sha256":"a3616a56b804a2b1e5e7a481fa83e3b25a7abef4cb9c7d86ac8751ad39a5c5dc"}}