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Paper Citation Record · LEDGER

Statistical inference for Linear Stochastic Approximation with Markovian Noise

As of 9 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 2026-08-09T06:31:02.800959+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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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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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Source-reported events for the cited work

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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 2026-08-09T06:31:02.800959+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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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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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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 2026-08-09T06:31:02.800959+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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

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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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source=pdf_text observed=2026-08-07T14:29:35.586841Z digest=sha256:7970c7a97d5a343851c9f80b62622f30b6b1f4d2a05bb29f204b7416e85ac3c3

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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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=sha256:163bc43dee4c6f315b4fbbae797638952fb8cf7119c966b7f0bf710e76900eee

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

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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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+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
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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 2026-08-09T06:31:02.800959+00:00.

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:36.150682Z digest=sha256:90b006f930b4b633129f5762f2812ef7a84e9aa3bf156e4a09073f2aab95e14d

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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source=pdf_text observed=2026-08-07T14:29:36.201689Z digest=sha256:723ff5a570cc7f4c434a684d332209706350298f914d2d85b2b6c67d794e5253

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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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:f699a1f799dc2e52a847e633a4d4d2c35ac61c2782bf199e5306a048653ff0c0

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 2026-08-09T06:31:02.800959+00:00.

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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
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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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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
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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 2026-08-09T06:31:02.800959+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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.043765Z digest=sha256:004805d8a40aac66a1aa9a020b9179934f477347bd0c1728ee1abe97d4d8b0f0

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
unresolved
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=sha256:790bf44cd42ef65025f1081cd1c1a1feebee37756787c4c67c6be9f26f550c15

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.187062Z digest=sha256:4d098c08404ad1c2ad790381de4846ede2d19b0385593e1b6bf405a6564a01d3

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
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.344766Z digest=sha256:9e7503188b36b295f1e020d774f1d9fb6ed0419e6f171a11ba2e34b001485942

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.411613Z digest=sha256:d4adeeea97c2a5a8ca1e9325469cf1a2404beb272318bb15ac2aed15ca14adee

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.485205Z digest=sha256:b8e836b49af86ff6f92319f68a551c04a8c26ac34e18ea2348c97e918986209f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.544375Z digest=sha256:b60759ca9000128252f5945e34da2a3e98460cdeade05f50591ef868a53d6d1a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.866480Z digest=sha256:357cdf2a908b40bde69730e88c2f189a84cde68530f3f18d4f9e6dd48544f980

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 2026-08-09T06:31:02.800959+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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:38.247440Z digest=sha256:4119571f02d50637c202fbf91630abe8d5e3ad70185783d8f05f01100cbefdde

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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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=sha256:84d5460577b3e7830c459a7631ed4b123f32dab0db5476f6804db70aff73647a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:38.589094Z digest=sha256:7cb459e8d1cd44caff7b90e73b98b91757850be75f8b44aca18bfe3497234479

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=sha256:7e223cbac3d47aab69a90d0f061c6bab99c91f827290f776ea5f17acf83a80da

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:38.892627Z digest=sha256:8989b9ede112c2ee699559380fc873ed465af5be462f9e4dd9891a056eade015

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:38.746978Z digest=sha256:8b2e75f441281cdc9dcc67cbe8edd95ef568c7b86579987ec769999b496128c4

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:39.129600Z digest=sha256:3240b7d20613340834ed405cdb25b5bb1dc762d14bf278da54342981c8f6cad5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:38.965842Z digest=sha256:6373f95d0af1419f37192d4590ff161d294646969a2bfda35afb66e5e2abc00e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:39.336887Z digest=sha256:0822baac59c0d2c1c935a705f3e122bf8d0394eb4a186efca8519653ae6d02a5

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:39.216870Z digest=sha256:0a3f33c9d76f9a5f12dbf0f0f211a85c6c6b4be28352eeca30db0d72197c4c94

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=sha256:72e8cbe5ce5f9c0d935821bf97e2c3d840e9b421a0131f9607df2e10cf596f20

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:39.432413Z digest=sha256:430ad098c03ead8e25f127f53d923904b5e2f257cb1a4ce5e26c9208f1289a58

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:39.770959Z digest=sha256:e59cc7bffd837fceddb3ee8bcae6f317ecd91894a8da0596a3e302360a1206a0

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:d31f94c57b54a3e3b1a3a29821529afd541d9b609e74d8ef63bd727814c12e39

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:d7dadc1b349edb81e354432f82285ffa6fc507e8b4502cba8833d44c789b59d8

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 2026-08-09T06:31:02.800959+00:00.

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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
unresolved
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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:40.251996Z digest=sha256:fc77702af9252953d8173977a5a354c253d67a9ed87c28a7bd9c1205daf74fc7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:40.398786Z digest=sha256:9b19b866d31e6df6a7aca9c5493acfcea1d1a9e85f49670f8da48638ab626255

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:40.563729Z digest=sha256:1435acc953a45c26a186d4d297fca565f5ce5556eb7e13b500f713b835c22a93

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

Resolution
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:40.725439Z digest=sha256:44dfbd934c63c04c53074c263c42e18425e19b9f4cf06552c29abf2a40c45be6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:40.846020Z digest=sha256:8dac57af86408c169b1f5f9a5ea61e24a45f24a853c76fff6907a32aba0b3f22

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:29:37.659444Z digest=sha256:9db77d95e15d6ced0e683c2f9c83ac77b01095c7a8e9f0c3949c208c8070ff75

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
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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T14:55:49.034505Z digest=sha256:9db4219a3208f831442b083c1a35131c23cae37d0b3ff0aeb03ff5dcada0b80e

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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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:c0a4cdf58b4c49e18bac7862078a6280221b8e4f90975c989b10238cb7023942

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:11:48.816106Z digest=sha256:985a6dd42e5812ae00e3eb99273eb7f885718fb2e809e5fe61158d81e55634b7

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T22:22:51.788055Z digest=sha256:f82e589ba62e8cd53cad8822eed5063a19d297e4afcc3ca3cfb1dea3c14c3f2b