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Paper Citation Record · LEDGER

Statistical inference for Linear Stochastic Approximation with Markovian Noise

As of 14 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 4 inbound Pith citation observations for arXiv:2505.19102.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.19102 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:29:40.846020Z

measured 98 of 98 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T10:46:25.335756Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T23:29:02.029526Z

Reference resolution

94 of 94 outbound references displayed

  • verified exact2
  • verified fuzzy52
  • unresolved37
  • parse uncertain1
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44787c73-49f1-480a-bd62-2e8ba95f1189 · outbound

This paper cites High-dimensional central limit theorems for linear functionals of online lea st-squares sgd.

Statistical inference for Linear Stochastic Approximation with Markovian Noise High-dimensional central limit theorems for linear functionals of online lea st-squares sgd

Reference 1

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Observation 525a6c04-be9c-4813-b8c9-8c53c2e8d743 · outbound

This paper cites On a per turbation approach for the analysis of stochastic tracking algorithms.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On a per turbation approach for the analysis of stochastic tracking algorithms

Reference 2

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Observation d7c58695-68bf-4424-a27c-cf7b52d8c488 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 3

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Observation 0e8931b5-f6da-43e4-8905-00bac64324ca · outbound

This paper cites On the generat ion of markov decision processes.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On the generat ion of markov decision processes

Reference 4

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Observation ef184d50-36e4-4404-aecf-3cd0251ddb59 · outbound

This paper cites A martingale decomp osition for quadratic forms of Markov chains (with applications).

Statistical inference for Linear Stochastic Approximation with Markovian Noise A martingale decomp osition for quadratic forms of Markov chains (with applications)

Reference 5

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Observation 565104f6-b2b4-4f5b-9aa1-0341b869147f · outbound

This paper cites Barsov and V.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Barsov and V

Reference 6

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Observation ca29ca38-5145-47cb-8131-f14fa5aeeed3 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 7

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Observation 8de54819-8dca-41a7-9196-8b959ac58aef · outbound

This paper cites Benveniste, M.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Benveniste, M

Reference 8

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Observation 025d5037-e3f3-4a48-9d87-7dd88ed8b820 · outbound

This paper cites Edgeworth expan sions of suitably normalized sample mean statistics for atomic markov chains.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Edgeworth expan sions of suitably normalized sample mean statistics for atomic markov chains

Reference 9

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Observation 527de3f7-ee67-4fe7-858f-6e25235bddc4 · outbound

This paper cites Bhandari, D.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bhandari, D

Reference 10

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Observation 7b2c594d-61f9-4156-a6d6-8410af8a21e8 · outbound

This paper cites Bolthausen.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bolthausen

Reference 11

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Observation 9bec9d41-b027-49ae-b998-384eb67a6c20 · outbound

This paper cites Bolthausen.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bolthausen

Reference 12

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Observation 3efba6e6-b241-4637-965a-18875d048719 · outbound

This paper cites The berry-esseen theorem for functi onals of discrete markov chains.

Statistical inference for Linear Stochastic Approximation with Markovian Noise The berry-esseen theorem for functi onals of discrete markov chains

Reference 13

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Observation 62aa3b15-96d6-492d-98eb-2c58fa9579ab · outbound

This paper cites Stochastic Approximation: A Dynamical Systems Viewpoint.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Stochastic Approximation: A Dynamical Systems Viewpoint

Reference 14

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Observation 026f21b1-7eab-401d-a64c-3144cb8a513f · outbound

This paper cites Statistical infere nce for online decision making via stochastic gradient descent.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Statistical infere nce for online decision making via stochastic gradient descent

Reference 15

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Observation 8935c2ec-338d-4a2e-8270-44faaf4c79dd · outbound

This paper cites Lee, Xin T.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Lee, Xin T

Reference 16

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Observation d9efb821-8e96-4911-a4e4-b17340b812f8 · outbound

This paper cites Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensiona l random vectors.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensiona l random vectors

Reference 17

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Observation b76437a8-ebb7-4ca4-93bf-df914cdd6c44 · outbound

This paper cites Central limit theorems and boot- strap in high dimensions.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Central limit theorems and boot- strap in high dimensions

Reference 18

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Observation 533e8c3d-38fa-4fb6-8c74-a63e50d7bf0e · outbound

This paper cites Strong consistency and other properti es of the spectral variance estimator.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Strong consistency and other properti es of the spectral variance estimator

Reference 19

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Observation 72f5e80d-e175-415e-b36c-ad76c2be9aad · outbound

This paper cites The total variation distance between high-dimensional Gaussians with the same mean.

Statistical inference for Linear Stochastic Approximation with Markovian Noise The total variation distance between high-dimensional Gaussians with the same mean

Reference 20

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Observation d96a5b35-901f-4540-9fea-5dd6711aefab · outbound

This paper cites Br idging the gap between constant step size stochastic gradient descent and Markov chains.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Br idging the gap between constant step size stochastic gradient descent and Markov chains

Reference 21

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Observation 14f45463-6c2b-4d1b-8ee9-458be7aef681 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 22

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Observation 7f89e58d-2170-41cd-92a4-1aec80313db9 · outbound

This paper cites Finite-time high- probability bounds for Polyak–Ruppert averaged iterates o f linear stochastic approximation.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Finite-time high- probability bounds for Polyak–Ruppert averaged iterates o f linear stochastic approximation

Reference 23

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Observation 8c0f0adb-b978-46fd-8f40-26eb285a6b63 · outbound

This paper cites Tight high probability bounds for linear stochastic ap proximation with fixed stepsize.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Tight high probability bounds for linear stochastic ap proximation with fixed stepsize

Reference 24

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Observation b6ecaff4-1588-42f3-aa35-2c71cf9f0933 · outbound

This paper cites Rosenthal-type inequalities for linear statistics of mark ov chains.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Rosenthal-type inequalities for linear statistics of mark ov chains

Reference 25

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Observation 0d8b45f6-6ac9-431e-a8b1-70f5bb5a3c08 · outbound

This paper cites On the stability of random matrix product with markovian noise: Ap plication to linear stochastic ap- proximation and td learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On the stability of random matrix product with markovian noise: Ap plication to linear stochastic ap- proximation and td learning

Reference 26

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Observation d6dd230d-c982-4984-a2b1-e4ea86d7c91d · outbound

This paper cites Bootstrap methods: another look at the j ackknife.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bootstrap methods: another look at the j ackknife

Reference 27

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Observation 1a15dad7-95cd-4989-b3af-eb4a59586929 · outbound

This paper cites Exact rates of convergence in some marting ale central limit theorems.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Exact rates of convergence in some marting ale central limit theorems

Reference 28

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Observation 28defdf5-f323-4f45-9401-0000900a79c7 · outbound

This paper cites Online bootstrap con fidence intervals for the stochastic gradient descent estimator.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online bootstrap con fidence intervals for the stochastic gradient descent estimator

Reference 29

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Observation a2b75984-f0c3-48bc-aa10-fdb442b99f31 · outbound

This paper cites Flegal and Galin L.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Flegal and Galin L

Reference 30

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 72bd623e-f7e3-4692-9628-49a6e117e07a · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 31

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Observation 6be1576a-3ba8-454f-b461-ed462d2f80f8 · outbound

This paper cites Neue herleitung und explizite restab schätzung der riemann-siegel-formel.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Neue herleitung und explizite restab schätzung der riemann-siegel-formel

Reference 32

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Observation 9a10b5b2-9787-478a-aba8-89276a4ee0da · outbound

This paper cites Off-policy lear ning with eligibility traces: a survey.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Off-policy lear ning with eligibility traces: a survey

Reference 33

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Source-reported events for the cited work

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Observation a83abfd8-c2e9-448c-90d5-5a2058bd0c33 · outbound

This paper cites Matrix concentration for products.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Matrix concentration for products

Reference 34

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d844c1c5-b4c2-4ccb-ae1a-f2481809b457 · outbound

This paper cites CryptSan: Leveraging ARM Pointer Authentication for Memory Safety in C/C++.

Statistical inference for Linear Stochastic Approximation with Markovian Noise CryptSan: Leveraging ARM Pointer Authentication for Memory Safety in C/C++

Reference 35

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Observation 1476cd96-9e0a-43ff-9554-c3967f5e728f · outbound

This paper cites Effective Berry-Esseen and concent ration bounds for Markov chains with a spectral gap.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Effective Berry-Esseen and concent ration bounds for Markov chains with a spectral gap

Reference 36

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raw_fallback, observed 2026-08-07T14:29:50.466287Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2a4e020d-7d6e-4386-937d-9a5a093c901c · outbound

This paper cites Actor-critic algorit hms.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Actor-critic algorit hms

Reference 37

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Observation 89b3a801-2de7-4b83-bcb6-9e2e29bf7737 · outbound

This paper cites The jackknife and the bootstrap for gener al stationary observations.

Statistical inference for Linear Stochastic Approximation with Markovian Noise The jackknife and the bootstrap for gener al stationary observations

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:50.192934Z

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Observation 5aa8b8cc-bfd4-4cc4-bc09-271d1abbc89f · outbound

This paper cites Stochastic approximation and recursive algorithms and applications, volume 35.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Stochastic approximation and recursive algorithms and applications, volume 35

Reference 39

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Observation 72ea55d2-4d5f-490c-8661-f15855884b96 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 40

Resolution
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raw_fallback, observed 2026-08-07T14:29:50.030061Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5121255c-8f41-4582-b762-d155a0e2096f · outbound

This paper cites Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data

Reference 41

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Observation de6077eb-4d1c-46c4-9d35-ff40024ea36c · outbound

This paper cites A statistical analysis of Polyak-Ruppert averaged Q-learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise A statistical analysis of Polyak-Ruppert averaged Q-learning

Reference 42

Resolution
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raw_fallback, observed 2026-08-07T14:29:49.905945Z

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Observation 0f2e42a7-0294-48f0-b366-5045c701b96e · outbound

This paper cites Statistical infe rence with Stochastic Gradient Meth- ods under φ-mixing Data.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Statistical infe rence with Stochastic Gradient Meth- ods under φ-mixing Data

Reference 43

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source=pdf_text observed=2026-08-07T14:29:35.876466Z digest=sha256:69c3a826ee1df90b3625c255067a7561d16c37e983156c1e4afda733878e0737

Observation cf9369ea-282e-4b67-8f66-302d80f414c2 · outbound

This paper cites Multiplier subsample bootstr ap for statistics of time series.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Multiplier subsample bootstr ap for statistics of time series

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:49.756271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6ef48a35-ba5f-4d98-b8b1-b001b50dcbf9 · outbound

This paper cites Exact converge nce rates in the central limit theorem for a class of martingales.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Exact converge nce rates in the central limit theorem for a class of martingales

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 78bf4a24-c31f-4dba-8767-dfb5c1f813e0 · outbound

This paper cites Overlapping batch m eans: Something for nothing? Technical report, Institute of Electrical and Electronics Engineers (IEEE), 1984.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Overlapping batch m eans: Something for nothing? Technical report, Institute of Electrical and Electronics Engineers (IEEE), 1984

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:49.455286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ff875aad-63af-452f-8a96-2418bab11270 · outbound

This paper cites Conver gence rate and averaging of nonlin- ear two-time-scale stochastic approximation algorithms.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Conver gence rate and averaging of nonlin- ear two-time-scale stochastic approximation algorithms

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:49.312089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:36.077698Z digest=sha256:77c96567e6c75755ce0e04ccfc3dc0c8b9707736d7b6af2cd6e97f2ce5610779

Observation a3395065-44e1-46d6-bc54-a76ccb9c9a92 · outbound

This paper cites On linear stochastic approximation: Fine-grained polyak- ruppert and non-asymptotic concen- tration.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On linear stochastic approximation: Fine-grained polyak- ruppert and non-asymptotic concen- tration

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:49.142009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:36.150682Z digest=sha256:cfd0a32070626634ad77da38cb0cbaea35a311539fe509a23f1474b889131539

Observation fbbb0398-fcbe-47ca-91c9-33a2b7423603 · outbound

This paper cites Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Optimal and instance-dependent guarantees for Markovian linear stochastic approximation

Reference 49

Resolution
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local_arxiv, observed 2026-08-07T14:29:41.556768Z

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Observation de543676-08ac-4755-b954-d4badd180ef3 · outbound

This paper cites Non-asymptotic analys is of stochastic approximation algo- rithms for machine learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Non-asymptotic analys is of stochastic approximation algo- rithms for machine learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:48.978889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:36.242779Z digest=sha256:6650e43a6594749fa04cd5789163aa6db0fe28fadbda4400ae0c7ad66ba39301

Observation d1cfc709-a2cd-4fb6-8d01-123d57883baf · outbound

This paper cites A note on concentration inequalities for the overlapped batch mean variance estimators for Markov chains.

Statistical inference for Linear Stochastic Approximation with Markovian Noise A note on concentration inequalities for the overlapped batch mean variance estimators for Markov chains

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:29:41.389262Z

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Observation 04e5ff78-fe04-4bf5-8edd-72a224316c76 · outbound

This paper cites Bootstrap confidence sets for spectral projectors of sample covariance.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bootstrap confidence sets for spectral projectors of sample covariance

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:48.582200Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:29:36.361727Z digest=sha256:b73169be55baca3e1bb9679c7aa23b6c152c9140650d26654fa7afa6b16b98aa

Observation 7265cfab-3fa2-4961-b070-b713a97ddc23 · outbound

This paper cites Robust stochas- tic approximation approach to stochastic programming.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Robust stochas- tic approximation approach to stochastic programming

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:48.401445Z

Source-reported events for the cited work

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Observation 0f65a538-fa3f-4e14-a23f-4648cf6e38cf · outbound

This paper cites Osekowski.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Osekowski

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:48.207163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:36.461475Z digest=sha256:5f8f4d8ea24174c97c15f13734a241111f2ea93bce49853de8a13b0bda2ce1b0

Observation bf2994ea-2532-494e-80a3-90690149c122 · outbound

This paper cites Finite time analysis of temporal difference learning with linear function approxi mation: Tail averaging and regulari- sation.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Finite time analysis of temporal difference learning with linear function approxi mation: Tail averaging and regulari- sation

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:47.848598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 05f99f8c-f6ed-450d-8f95-b4c6b092c91f · outbound

This paper cites Concentration inequalities for Markov chains by Marton couplings and spectral methods.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Concentration inequalities for Markov chains by Marton couplings and spectral methods

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:47.720285Z

Source-reported events for the cited work

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Observation c488ecec-03f1-421f-be59-1d183ec0f546 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:29:47.599208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b14a9d19-8920-4eed-bc0f-94a8aa34a11c · outbound

This paper cites Optimum Bounds for the Distributions of Martingales in Banach Spaces.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Optimum Bounds for the Distributions of Martingales in Banach Spaces

Reference 58

Resolution
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raw_fallback, observed 2026-08-07T14:29:47.484119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e97ffe09-3bfe-4e7e-b0f8-70c34dcff6e5 · outbound

This paper cites Acceleration of s tochastic approximation by averaging.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Acceleration of s tochastic approximation by averaging

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:47.348984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2edb4ad4-e1b6-43d2-8f8c-9465fca64353 · outbound

This paper cites Making gradient descent optimal for strongly convex stochastic optimization.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Making gradient descent optimal for strongly convex stochastic optimization

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:47.164468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9771468f-42a9-4379-81b1-d73a14a54626 · outbound

This paper cites Online bootstrap inference for policy evaluation in reinforcement learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online bootstrap inference for policy evaluation in reinforcement learning

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:47.003482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:36.889170Z digest=sha256:955da60391477cd49a8ade25fe45390c062ca15619be09b437dbb33814d48ce4

Observation 800d2550-504c-4dc9-9a37-aeb8e89f0c79 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 62

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:29:46.802772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 55d75244-579b-4a6c-8b11-d203fdde1f7f · outbound

This paper cites Rosenthal.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Rosenthal

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:46.618537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 57ff8020-e00c-4a3e-9ed2-971d566c77ae · outbound

This paper cites Fundamentals of Stein’s method.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Fundamentals of Stein’s method

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:46.474870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e3c85025-0cf9-434b-85ac-6e68919fe115 · outbound

This paper cites Online covariance estimation for stochastic gradient descent under Markovian sampling.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online covariance estimation for stochastic gradient descent under Markovian sampling

Reference 65

Resolution
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no resolver link, observed 2026-08-07T14:29:37.107434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:37.107434Z digest=sha256:dc7e85907388df49fc59330b6dd72d70d6a4b46cde0c832afd29718c6d654f26

Observation 74f71616-0131-4041-893f-463601fc976c · outbound

This paper cites The bayesian bootstrap.

Statistical inference for Linear Stochastic Approximation with Markovian Noise The bayesian bootstrap

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:46.305862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c889924c-1334-4354-8419-54577f38faf1 · outbound

This paper cites Efficient estimations from a slowly conv ergent robbins-monro process.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Efficient estimations from a slowly conv ergent robbins-monro process

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:46.124196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation bbdc196b-8a92-450a-a77b-a8eae8ff3849 · outbound

This paper cites On quantitative bounds in the mean marti ngale central limit theorem.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On quantitative bounds in the mean marti ngale central limit theorem

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:45.944041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:37.411613Z digest=sha256:335e20c27c394c66cf4c551b76f72d4946afa990f37374a14f358bd30a0ff744

Observation 2c5ff85c-09fe-4d77-a69a-0ef3b3a8fcd8 · outbound

This paper cites Gaussian Approximation and Multiplier Bootstrap for P olyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Gaussian Approximation and Multiplier Bootstrap for P olyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:45.747931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:37.485205Z digest=sha256:2e6fcb54c35e3bb7f9c32498756343c61e947ec4c6255a5431ef71c9427cf235

Observation c369e3b3-85ce-4865-80d3-7619e4ebbc0c · outbound

This paper cites Improved High- Probability Bounds for the Temporal Difference Learning Al gorithm via Exponential Stabil- ity.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Improved High- Probability Bounds for the Temporal Difference Learning Al gorithm via Exponential Stabil- ity

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:45.537962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:37.544375Z digest=sha256:ee7b217674b4e966e161450239d3ee6edf7d4bcc7d8ed3041dc41888319387df

Observation c2491052-7c5c-499e-8375-20bde456b00f · outbound

This paper cites Berry–Esseen bounds f or multivariate nonlinear statis- tics with applications to M-estimators and stochastic grad ient descent algorithms.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Berry–Esseen bounds f or multivariate nonlinear statis- tics with applications to M-estimators and stochastic grad ient descent algorithms

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:45.188057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:37.866480Z digest=sha256:a82354ce0ac72df59a033c344704095450c67542cbe7bc289c72b47d493a76ec

Observation 4885cd77-d9f5-4d4c-9d22-ed286aa0ce95 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:29:48.013956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation bd420bb2-a348-4903-9656-abdfb7ab970b · outbound

This paper cites Bootstrap confide nce sets under model misspecifica- tion.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Bootstrap confide nce sets under model misspecifica- tion

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:45.058405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:38.247440Z digest=sha256:350738109e9319c7bee7502990867467de5bd34a51713a5f391485ad6af6ff05

Observation f1cd4284-90a0-41ba-af8f-8a6a052be8f9 · outbound

This paper cites Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent

Reference 74

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unresolved
no resolver link, observed 2026-08-07T14:29:38.017350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:38.017350Z digest=sha256:5cbfa789bca15d53ffaf821ede0450b26be364c9227aa7432156e8b9f9f0ea4c

Observation eab45e56-7f1a-406a-b3c5-80244d4607db · outbound

This paper cites Srikant and L.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Srikant and L

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:44.831105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:38.589094Z digest=sha256:8f51a74483404a135c0f23b3001ef397c24cd0e58a2257fc293c5187c65ff368

Observation ea381148-26b3-4ef3-a935-59b86c46907b · outbound

This paper cites Rates of Convergence in the Central Limit The orem for Markov Chains, with an Application to TD Learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Rates of Convergence in the Central Limit The orem for Markov Chains, with an Application to TD Learning

Reference 76

Resolution
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no resolver link, observed 2026-08-07T14:29:38.396754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:38.396754Z digest=sha256:6e531399103d3ab6e90486417d3b5b1010642734543cee613d596cea7b4d9b1d

Observation 4174fe58-7ed1-42ba-8cd8-3a058f0e6d05 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 77

Resolution
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raw_fallback, observed 2026-08-07T14:29:44.361337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:38.892627Z digest=sha256:711b3dfdb4f4c7dfd48282587790634c4f1a24f1b206544dab14f39e4aa7811f

Observation cd93ac2d-fda5-4b94-a92d-e4b251647005 · outbound

This paper cites S Sutton.

Statistical inference for Linear Stochastic Approximation with Markovian Noise S Sutton

Reference 78

Resolution
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raw_fallback, observed 2026-08-07T14:29:44.598521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:38.746978Z digest=sha256:d5e0447926d5ddd9428bfe522c88c88451416a8e69379b0e113af4ca75890c79

Observation 7dc57a48-99d5-4d65-be2a-00d346b25aa8 · outbound

This paper cites Probability in High Dimension.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Probability in High Dimension

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:43.883432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:39.129600Z digest=sha256:b23b8f5f95af14f45ff9b5b54b2babec780dd5240c1b24a3daec894528c34b46

Observation 54dcbc0d-c7e8-4a02-b681-c917c1efa5b2 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 80

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:29:44.165653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:38.965842Z digest=sha256:41c29237c46cc8146e9d4a1750485dd7fb127a6b717d6269800695fb10af1bca

Observation b9ae9242-fa90-4646-a60a-d666bccabe47 · outbound

This paper cites Watkins and P.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Watkins and P

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:43.487148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:39.336887Z digest=sha256:a49dcbcb6f385e7ff36a83d4a794121690afe5bf13b2a8ce7b041fad3a237974

Observation 473bb23d-3306-404d-beb0-5cd624ebbcb3 · outbound

This paper cites Online Covariance Ma trix Estimation in Stochastic Gradient Descent.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online Covariance Ma trix Estimation in Stochastic Gradient Descent

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:43.676028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:39.216870Z digest=sha256:7811a5c11a31ad4d5c413f909515dcacf2303686c49ff7d04f2ec5cba874cde9

Observation 8a321498-56ae-4e11-9534-dde4e516619c · outbound

This paper cites Statistical Inference for Policy Evaluation with Temporal Difference Learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Statistical Inference for Policy Evaluation with Temporal Difference Learning

Reference 83

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unresolved
no resolver link, observed 2026-08-07T14:29:39.522444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:39.522444Z digest=sha256:bc0bb87c729b631096242b42ac14cb77e38339f8ab8880fb05a238d75e6c93bf

Observation be0e5fa0-d550-4a69-a883-bfa626d8bb9f · outbound

This paper cites On the relationship between batch means, overlapping means and spectral estimation.

Statistical inference for Linear Stochastic Approximation with Markovian Noise On the relationship between batch means, overlapping means and spectral estimation

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:43.259939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:39.432413Z digest=sha256:e6102d5c9ef77b4320254d76524671f0ca974d127be0301e204874313125f76c

Observation 333249b1-6da7-4c22-b243-fe87884fe1bf · outbound

This paper cites Rates of convergence for empirical processes of stationary mixing sequences.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Rates of convergence for empirical processes of stationary mixing sequences

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:43.116292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:39.770959Z digest=sha256:a2641098a0c2c57dda035645272d0dfa95b08a3613ce3089049b85285b4cd9ef

Observation c8d03425-d406-4ddd-9edc-d89edcab8f00 · outbound

This paper cites Uncertainty quantification for Markov chain induced martingales with application to temporal difference learning.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Uncertainty quantification for Markov chain induced martingales with application to temporal difference learning

Reference 86

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no resolver link, observed 2026-08-07T14:29:39.620052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:39.620052Z digest=sha256:5efab48a9dfce5b8fc6ba6b85ed8bfe77896e4ed303f66421cfa49ab66f6ae59

Observation 0468889c-c9fe-42ff-a5c3-84126244afbc · outbound

This paper cites Online Bootstrap Inference with Nonconvex Stochastic Gradient Descent Estimator.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Online Bootstrap Inference with Nonconvex Stochastic Gradient Descent Estimator

Reference 88

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no resolver link, observed 2026-08-07T14:29:39.913050Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:29:39.913050Z digest=sha256:9657ff5bbbf5696f633580278ffb41c4f94b399b26ad881f63a61c2010a74e6e

Observation ad6b0d3d-2c4d-49f5-89b4-3598d9b089b3 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 89

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raw_fallback, observed 2026-08-07T14:29:42.929837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.054061Z digest=sha256:804f22f1d1a6579c10de9a396f1fb0b66ea3d2589899937daa906245e6066d17

Observation abec54f0-256f-41de-b100-8b270a1fe926 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 90

Resolution
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raw_fallback, observed 2026-08-07T14:29:42.814622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.251996Z digest=sha256:e3227679a9738fb2ee20e874f0548c63fe16c339176467adf3f8ad60205c25b7

Observation b7261cd0-47af-43cd-b261-489d50a6f9b6 · outbound

This paper cites We control β-mixing coefficient via total variation distance, see [22, Theorem F.3.3].

Statistical inference for Linear Stochastic Approximation with Markovian Noise We control β-mixing coefficient via total variation distance, see [22, Theorem F.3.3]

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:29:42.650729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.398786Z digest=sha256:1fe6492c8320d28a43381e815067fe4ae8d0c3ee8598092188989a4787e63785

Observation a7061c37-82d5-42f4-8da8-e9470de9524e · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 92

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T14:29:42.478711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.563729Z digest=sha256:2d309c8bb55ae32f13219c7a2337d22e8098e2ff773e680c2fe56f4b0ceac4d1

Observation 0d885ba6-7ca9-4ac8-8c7c-afe655d696ec · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 93

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unresolved
raw_fallback, observed 2026-08-07T14:29:42.330606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.725439Z digest=sha256:c4f58e6f709fc72cafd68468a6fb73b4b2a732b6a7104ab3f5153002aacbb2af

Observation 87d7683d-bc69-47e6-ae2f-702893ada3ef · outbound

This paper cites , k} k∑ i=m+1 αi ≥ c0 2(1 − γ) ((k + k0)1−γ − (m + k0)1−γ) , Proof.

Statistical inference for Linear Stochastic Approximation with Markovian Noise , k} k∑ i=m+1 αi ≥ c0 2(1 − γ) ((k + k0)1−γ − (m + k0)1−γ) , Proof

Reference 94

Resolution
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raw_fallback, observed 2026-08-07T14:29:42.205625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:40.846020Z digest=sha256:3dc1caee0214c47673685f391d81ce9b2ca61e1a5ce8b3599f2d1b5b0724ea90

Observation 508be250-7435-4fdb-bb4b-8830d7a691c0 · outbound

This paper cites an unresolved cited work.

Statistical inference for Linear Stochastic Approximation with Markovian Noise Unresolved cited work

Reference 4547

Resolution
parse uncertain
raw_fallback, observed 2026-08-07T14:29:45.333069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:29:37.659444Z digest=sha256:87025648d680c34128f03eda4c57ccb64c052872aeee41150caffb5d5f992067

Pith citing papers

Observation 743ec649-ab08-46ac-807f-755e006dba50 · inbound

Central Limit Theorems for Asynchronous Averaged Q-Learning cites this paper.

Central Limit Theorems for Asynchronous Averaged Q-Learning Statistical inference for Linear Stochastic Approximation with Markovian Noise

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:56:30.383561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T14:55:49.034505Z digest=sha256:733bba45c4d3f9a899735baf32f68568ac11b10f0fec6758995b8e4de84dde4c

Observation 54afbaa0-dddf-49ec-ab1f-626face77ea2 · inbound

Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization cites this paper.

Sharp asymptotic theory for Q-learning with LDTZ learning rate and its generalization Statistical inference for Linear Stochastic Approximation with Markovian Noise

Reference 54

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unresolved
no resolver link, observed 2026-07-13T10:46:25.335756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T10:46:25.335756Z digest=sha256:95efbc836734354192fa99a4a41baee9da0a66cfda56a73bf5511ee3624f458b

Observation 5b64ad4c-5317-43c5-ab7e-eeb96956a16b · inbound

Gaussian Approximation for Asynchronous Q-learning cites this paper.

Gaussian Approximation for Asynchronous Q-learning Statistical inference for Linear Stochastic Approximation with Markovian Noise

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:25:59.943910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T17:11:48.816106Z digest=sha256:3ebf557cd3e7ecf5659a855747a380959501a8d35b5991ed8be175e3d94f370c

Observation cfb9153a-5e37-4c0d-b15c-9219a9a409ad · inbound

A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise cites this paper.

A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise Statistical inference for Linear Stochastic Approximation with Markovian Noise

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:29:02.031103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-26T22:22:51.788055Z digest=sha256:20ae0d5fec41c837e6e70e9835cdb613a27b8f57e585716af577ff44ebf8602e