Paper Citation Record · LEDGER

Adaptive Estimation of the Transition Density of Controlled Markov Chains

As of 15 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 2 inbound Pith citation observations for arXiv:2505.14458.

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

pith.paper-citation-record.v1
2505.14458 v1

Coverage vector

measured 85 of 85 reference resolution

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measured 87 of 87 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-07T13:27:05.081050Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

85 of 85 outbound references displayed

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External citation measurements

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arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation f0395d91-51de-4da4-88f5-e09629ad1107 · outbound

This paper cites Inhomogeneous and anisotropic conditional density estimation from dependent data.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Inhomogeneous and anisotropic conditional density estimation from dependent data

Reference 1

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Observation 5ab058a8-934f-4dff-b089-a301c28dbadc · outbound

This paper cites An elementary view of Euler’s summation formula.

Adaptive Estimation of the Transition Density of Controlled Markov Chains An elementary view of Euler’s summation formula

Reference 2

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Observation 4501858e-75c2-426f-a575-6696f0d005ec · outbound

This paper cites Ash and Catherine A.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Ash and Catherine A

Reference 3

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This paper cites Kernel Estimation for Real-Valued Markov Chains.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Kernel Estimation for Real-Valued Markov Chains

Reference 4

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This paper cites CLT and Edgeworth Expansion for m-out-of-n Bootstrap Estimators of The Studentized Median.

Adaptive Estimation of the Transition Density of Controlled Markov Chains CLT and Edgeworth Expansion for m-out-of-n Bootstrap Estimators of The Studentized Median

Reference 5

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This paper cites Goggin’s corrected Kalman Filter: Guarantees and Filtering Regimes.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Goggin’s corrected Kalman Filter: Guarantees and Filtering Regimes

Reference 6

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Observation d31c601e-68b2-4d04-9433-b888fd96f5c2 · outbound

This paper cites Off-line Estimation of Controlled Markov Chains: Minimaxity and Sample Complexity.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Off-line Estimation of Controlled Markov Chains: Minimaxity and Sample Complexity

Reference 7

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This paper cites A new method for estimation and model selection:$$ \rho $$- estimation.

Adaptive Estimation of the Transition Density of Controlled Markov Chains A new method for estimation and model selection:$$ \rho $$- estimation

Reference 8

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This paper cites Estimator selection with respect to Hellinger-type risks.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Estimator selection with respect to Hellinger-type risks

Reference 9

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This paper cites Estimating the intensity of a random measure by histogram type estimators.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Estimating the intensity of a random measure by histogram type estimators

Reference 10

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Observation e16f49e3-f025-43a1-99b0-7a43a3a6b34e · outbound

This paper cites Rho-estimators revisited: General theory and applications.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Rho-estimators revisited: General theory and applications

Reference 11

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This paper cites Risk bounds for model selection via penaliza- tion.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Risk bounds for model selection via penaliza- tion

Reference 12

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Observation b71c3789-cebc-4920-95b1-ddc08036d7c9 · outbound

This paper cites Interpolation Spaces: An Introduction.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Interpolation Spaces: An Introduction

Reference 13

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This paper cites Occupation measures for controlled Markov processes: char- acterization and optimality.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Occupation measures for controlled Markov processes: char- acterization and optimality

Reference 14

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Observation cd303cb6-8394-44cb-bdcf-a002d31c3520 · outbound

This paper cites Explicit Constraints on the Geometric Rate of Convergence of Random Walk Metropolis-Hastings.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Explicit Constraints on the Geometric Rate of Convergence of Random Walk Metropolis-Hastings

Reference 15

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Observation 523e4735-c167-45f9-960c-c302eafa077d · outbound

This paper cites Statistical methods in Markov chains.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Statistical methods in Markov chains

Reference 16

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Observation cb8b397d-0b6b-4124-9137-ddcc74d81984 · outbound

This paper cites Model selection via testing: an alternative to (penalized) maximum likelihood estima- tors.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Model selection via testing: an alternative to (penalized) maximum likelihood estima- tors

Reference 17

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This paper cites Topics in controlled Markov chains.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Topics in controlled Markov chains

Reference 18

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This paper cites Basic Properties of Strong Mixing Conditions. A Survey and Some Open Ques- tions.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Basic Properties of Strong Mixing Conditions. A Survey and Some Open Ques- tions

Reference 19

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This paper cites Some Examples of Mixing Random Fields.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Some Examples of Mixing Random Fields

Reference 20

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Observation ade67df2-e1a7-4982-9652-7d288bd5536b · outbound

This paper cites On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis.

Adaptive Estimation of the Transition Density of Controlled Markov Chains On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis

Reference 21

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This paper cites Trade-off Between Dependence and Complexity for Nonparametric Learning -- an Empirical Process Approach.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Trade-off Between Dependence and Complexity for Nonparametric Learning -- an Empirical Process Approach

Reference 22

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This paper cites Degree of Adaptive Approximation.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Degree of Adaptive Approximation

Reference 23

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This paper cites Central Limit Theorem for Nonstationary Markov Chains. I.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Central Limit Theorem for Nonstationary Markov Chains. I

Reference 24

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Central Limit Theorem for Nonstationary Markov Chains. II

Reference 25

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

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This paper cites Probability inequalities related to Markov’s theorem.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Probability inequalities related to Markov’s theorem

Reference 27

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This paper cites On a New Characterization of Harris Recurrence for Markov Chains and Processes.

Adaptive Estimation of the Transition Density of Controlled Markov Chains On a New Characterization of Harris Recurrence for Markov Chains and Processes

Reference 28

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Observation eaf9c859-165a-40ad-addb-f5c679bde744 · outbound

This paper cites Wide-sense regeneration for Harris recurrent Markov processes: an open prob- lem.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Wide-sense regeneration for Harris recurrent Markov processes: an open prob- lem

Reference 29

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This paper cites Convergence of filters with applications to the Kalman-Bucy case.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Convergence of filters with applications to the Kalman-Bucy case

Reference 30

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Observation 19207183-f5df-4eac-8703-01f6e03e082b · outbound

This paper cites Probability: a graduate course.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Probability: a graduate course

Reference 31

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This paper cites Weak ergodicity in non-homogeneous Markov chains.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Weak ergodicity in non-homogeneous Markov chains

Reference 32

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This paper cites Recurrence con- ditions for Markov decision processes with Borel state space: a survey.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Recurrence con- ditions for Markov decision processes with Borel state space: a survey

Reference 33

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Observation 7b18a6de-75d7-4420-8ead-e32649c482f6 · outbound

This paper cites Using Reward Machines for High-Level Task Specification and Decom- position in Reinforcement Learning.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Using Reward Machines for High-Level Task Specification and Decom- position in Reinforcement Learning

Reference 34

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This paper cites Concentration inequalities for dependent random variables via the martingale method.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Concentration inequalities for dependent random variables via the martingale method

Reference 35

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Observation 68f67923-8468-4f78-abcc-b6bbc241869d · outbound

This paper cites Partially Observed Markov Decision Processes: From Filtering to Controlled Sensing.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Partially Observed Markov Decision Processes: From Filtering to Controlled Sensing

Reference 36

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This paper cites Adaptive estimation of the transition density of a Markov chain.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Adaptive estimation of the transition density of a Markov chain

Reference 37

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This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 38

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Adaptive Estimation of the Transition Density of Controlled Markov Chains System identification (2nd ed.): theory for the user

Reference 39

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Observation 1b596b40-daba-4b44-b96b-3fa3776b8348 · outbound

This paper cites Spectral thresholding for the estimation of Markov chain transition operators.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Spectral thresholding for the estimation of Markov chain transition operators

Reference 40

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Active Learning for Nonlinear System Identification with Guarantees

Reference 41

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Concentration Inequalities and Model Selection

Reference 42

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This paper cites On the local limit theorems for lower psi- mixing Markov chains.

Adaptive Estimation of the Transition Density of Controlled Markov Chains On the local limit theorems for lower psi- mixing Markov chains

Reference 43

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Adaptive Estimation of the Transition Density of Controlled Markov Chains On the local limit theorems for psi- mixing Markov chains

Reference 44

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This paper cites Bernstein inequality and moderate de- viations under strong mixing conditions.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Bernstein inequality and moderate de- viations under strong mixing conditions

Reference 45

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Markov chains and stochastic stability

Reference 46

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Adaptive Estimation of the Transition Density of Controlled Markov Chains The Importance of Non-Markovianity in Maximum State Entropy Exploration

Reference 47

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Adaptive Estimation of the Transition Density of Controlled Markov Chains A User’s Guide to Measure Theoretic Probability

Reference 48

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Observation f1baf2c9-4811-4138-b26f-fdfe51a7054a · outbound

This paper cites Asymptotic Theory of Weakly Dependent Random Processes.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Asymptotic Theory of Weakly Dependent Random Processes

Reference 49

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Reference 50

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Adaptive Estimation of the Transition Density of Controlled Markov Chains Density estimation under local differential privacy and Hellinger loss

Reference 51

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Reference 52

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Observation 3112c406-ff2d-4033-a976-284ce1fe4507 · outbound

This paper cites Modeling Medical Treatment Using Markov Decision Processes.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Modeling Medical Treatment Using Markov Decision Processes

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:08.779058Z

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Observation a67ecb48-2853-4d17-96c1-b7d0793ec89e · outbound

This paper cites Semi-stationary processes.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Semi-stationary processes

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:08.597450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3240a445-c635-41f0-a561-97669bc00a3f · outbound

This paper cites Reinforcement learning: An introduction.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Reinforcement learning: An introduction

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:56.964883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bed60da-17b5-492d-ae65-a99871323ba9 · outbound

This paper cites Estimation of the transition density of a Markov chain.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Estimation of the transition density of a Markov chain

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:09.036797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 06875985-4bd3-4dab-a9c6-1f3223eb239b · outbound

This paper cites On the Foundation of Distributionally Robust Reinforcement Learning.

Adaptive Estimation of the Transition Density of Controlled Markov Chains On the Foundation of Distributionally Robust Reinforcement Learning

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:08.133486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9eda7874-00bb-4eda-bf75-9acd14c1df0b · outbound

This paper cites Products of Indecomposable, Aperiodic, Stochastic Matrices.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Products of Indecomposable, Aperiodic, Stochastic Matrices

Reference 58

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:43:07.901739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 77c05951-d663-404e-ab89-292ffbd728d8 · outbound

This paper cites Online Adversarial Stabilization of Unknown Linear Time-Varying Systems.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Online Adversarial Stabilization of Unknown Linear Time-Varying Systems

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:57.636584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d661081-57bf-488c-9d37-731d074e39bb · outbound

This paper cites Introduction to Nonparametric Estimation.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Introduction to Nonparametric Estimation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:08.360753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d0610a55-3fd5-4d9e-b68b-51755106ae3d · outbound

This paper cites Furthermore, P m∈M∞ e−|m| ≤ P l≥0 2l(2d1+d2)e−2l(2d1+d2) ≤ 15, and for any m ∈ Ml, |m| ≤2l(2d1+d2) where |m| is the cardinality of the partition m.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Furthermore, P m∈M∞ e−|m| ≤ P l≥0 2l(2d1+d2)e−2l(2d1+d2) ≤ 15, and for any m ∈ Ml, |m| ≤2l(2d1+d2) where |m| is the cardinality of the partition m

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:07.706226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 88f4194c-e39f-45ca-bcb3-ad2d0a42c1c9 · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:07.485396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c1f81a86-bb8d-42c4-8e17-8b38e731ce99 · outbound

This paper cites , Kl} ∈S m∈Ml m such that K ⊂ Ki, i∈ {1,.

Adaptive Estimation of the Transition Density of Controlled Markov Chains , Kl} ∈S m∈Ml m such that K ⊂ Ki, i∈ {1,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:07.173560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 39ea561d-a6f4-4fc7-8cec-3ef5e4b41a4b · outbound

This paper cites To be precise, m ∨ m′ = [ K′∈m′ m ∨ K′ (A.1) where m ∨ K′ is as defined in eq.

Adaptive Estimation of the Transition Density of Controlled Markov Chains To be precise, m ∨ m′ = [ K′∈m′ m ∨ K′ (A.1) where m ∨ K′ is as defined in eq

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.930143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c11fc3e3-8d85-403c-9bd9-0e84169db541 · outbound

This paper cites Sincepen(m) = L(1.5+log n)|m|/n, and |χ×I×χ| = 1 −2 − L(1.5 + logn)/n ≤ 3 − L(1.5 + logn)|m⋆ 2 ∨ K|/n.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Sincepen(m) = L(1.5+log n)|m|/n, and |χ×I×χ| = 1 −2 − L(1.5 + logn)/n ≤ 3 − L(1.5 + logn)|m⋆ 2 ∨ K|/n

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.650985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f24b48fe-142c-42fa-8948-2b42f16df677 · outbound

This paper cites Hence, with probability at most exp − n pen(m1)+pen(m2) κ − n ζ , 1 − 1√ 2 H2 s, f2 + T f1, f2 − 1 + 1√ 2 H2 s, f1 ≤ 1 4 1 − 1√ 2 h H2 s, f2 + H2 s, f1 i + xκ n.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Hence, with probability at most exp − n pen(m1)+pen(m2) κ − n ζ , 1 − 1√ 2 H2 s, f2 + T f1, f2 − 1 + 1√ 2 H2 s, f1 ≤ 1 4 1 − 1√ 2 h H2 s, f2 + H2 s, f1 i + xκ n

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.295063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c9d28a15-6d99-459c-a08b-757d8f3a9ea8 · outbound

This paper cites We prove 3.

Adaptive Estimation of the Transition Density of Controlled Markov Chains We prove 3

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:06.003439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8be43c2f-dd36-416e-a2ce-e00ab03a0c43 · outbound

This paper cites (A.1) m ∨ m′ = [ K′∈m′ m ∨ K′ where m ∨ K′ := K′ ∩ K : K ∈ m, K′ ∩ K ̸= Ø.

Adaptive Estimation of the Transition Density of Controlled Markov Chains (A.1) m ∨ m′ = [ K′∈m′ m ∨ K′ where m ∨ K′ := K′ ∩ K : K ∈ m, K′ ∩ K ̸= Ø

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:05.608148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9802bbe8-7869-4e9d-b2bf-18fed51159f9 · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 74

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:05.422080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 016a5648-3a62-4db6-b167-3823e29cc49f · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:05.150307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 61ad21b6-d64a-423f-8da1-ea9aaf115c47 · outbound

This paper cites This gives us the required result.

Adaptive Estimation of the Transition Density of Controlled Markov Chains This gives us the required result

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:04.929692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f332146e-1823-4374-ba17-c31aaaf64d57 · outbound

This paper cites (B.26) Then, R(n) ≤ 4/n 40.

Adaptive Estimation of the Transition Density of Controlled Markov Chains (B.26) Then, R(n) ≤ 4/n 40

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:04.680490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 428d65df-dcfa-41e0-8dc8-69673106b077 · outbound

This paper cites Broadly, our strategy is to pose the question of tightness of R(n) in terms of sample complexity, and then follow the usual techniques from [56] to show minimaxity.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Broadly, our strategy is to pose the question of tightness of R(n) in terms of sample complexity, and then follow the usual techniques from [56] to show minimaxity

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:04.486558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d33ac922-1e62-4075-b0a1-fdabc624bac3 · outbound

This paper cites , d1/3}, the expected return time T as defined in definition 4 satisfies T (S) = 4 5ι2Vol(S).

Adaptive Estimation of the Transition Density of Controlled Markov Chains , d1/3}, the expected return time T as defined in definition 4 satisfies T (S) = 4 5ι2Vol(S)

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:04.309400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 218e7fa5-925e-4498-b72f-01d7290a20f0 · outbound

This paper cites In particular, cp as written in Assumption 1 is only depends upon ι.

Adaptive Estimation of the Transition Density of Controlled Markov Chains In particular, cp as written in Assumption 1 is only depends upon ι

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:04.090968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 201eda6a-7107-405b-9648-96d98cadcee5 · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:03.902419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7aa9b953-e5c6-42bf-ad2b-397e166feebd · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:03.689593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9556504b-afe5-432d-adb3-82f9f6fa6238 · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 83

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T15:43:03.453906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80758fd2-de73-4fad-aa5c-9ac733ed4d66 · outbound

This paper cites (√s − p ¯f )2 ¯f + 1 # = 2 ¯f.

Adaptive Estimation of the Transition Density of Controlled Markov Chains (√s − p ¯f )2 ¯f + 1 # = 2 ¯f

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:03.212152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1bbe70e2-c2e6-4e8d-931c-cba7df78c8a9 · outbound

This paper cites n−1X i=0 1 Sr (Xi, ai) #) = [ Sr∈m(2) ref ( − n 2 νn(Sr) ≥ n−1X i=0 1 Sr (Xi, ai) − E.

Adaptive Estimation of the Transition Density of Controlled Markov Chains n−1X i=0 1 Sr (Xi, ai) #) = [ Sr∈m(2) ref ( − n 2 νn(Sr) ≥ n−1X i=0 1 Sr (Xi, ai) − E

Reference 85

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:43:03.037635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d703461f-d83e-4f14-9653-086a2eef2f21 · outbound

This paper cites DOI: 10.1007/1-4020-8066-2_23.

Adaptive Estimation of the Transition Density of Controlled Markov Chains DOI: 10.1007/1-4020-8066-2_23

Reference 612

Resolution: verified exact; doi, observed 2026-08-07T15:43:00.538732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3b684cbd-a168-499b-ab8f-da1dd81744cb · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 1999

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T15:43:10.127894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecb6e7f0-6706-4373-84b0-dfaaaf68ac5b · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 2000

Resolution: parse uncertain; no resolver link, observed 2026-08-07T15:42:51.387467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdf31e3a-7964-444c-bc40-77b90582c748 · outbound

This paper cites On the Foundation of Distributionally Robust Reinforcement Learning.

Adaptive Estimation of the Transition Density of Controlled Markov Chains On the Foundation of Distributionally Robust Reinforcement Learning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:57.347174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4604db3f-0edc-4092-b6fe-87ea9ecde5b9 · outbound

This paper cites an unresolved cited work.

Adaptive Estimation of the Transition Density of Controlled Markov Chains Unresolved cited work

Reference 2064

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:52.656029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 085970f3-2a0f-437e-abc5-d29b6a187922 · inbound

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity cites this paper.

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity Adaptive Estimation of the Transition Density of Controlled Markov Chains

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-09T03:25:15.036464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a6dd3002-744c-477b-af38-1d0c6b5ed73d · inbound

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity cites this paper.

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity Adaptive Estimation of the Transition Density of Controlled Markov Chains

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:56:26.470122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.