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Paper Citation Record · LEDGER

Statistical and Algorithmic Foundations of Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 100 of 162 outbound references and 1 inbound Pith citation observation for arXiv:2507.14444.

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

pith.paper-citation-record.v1
2507.14444 v1

Coverage vector

measured 100 of 162 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:15:15.850895Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 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

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Source: cited_works

Reference resolution

100 of 162 outbound references displayed

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  • verified fuzzy7
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Outbound references

Observation 12693451-7cd5-408e-802e-84f3cd7406ac · outbound

This paper cites CS Dept., UW Seattle, Seattle, WA, USA, Tech.

Statistical and Algorithmic Foundations of Reinforcement Learning CS Dept., UW Seattle, Seattle, WA, USA, Tech

Reference 1

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This paper cites Advances in neural information processing systems 33:20095–20107.

Statistical and Algorithmic Foundations of Reinforcement Learning Advances in neural information processing systems 33:20095–20107

Reference 2

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Statistical and Algorithmic Foundations of Reinforcement Learning Unresolved cited work

Reference 3

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This paper cites Journal of Machine Learning Research 22(98):1–76.

Statistical and Algorithmic Foundations of Reinforcement Learning Journal of Machine Learning Research 22(98):1–76

Reference 4

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This paper cites Advances in neural information processing systems 19.

Statistical and Algorithmic Foundations of Reinforcement Learning Advances in neural information processing systems 19

Reference 5

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Statistical and Algorithmic Foundations of Reinforcement Learning Unresolved cited work

Reference 6

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This paper cites International Conference on Machine Learning , 263–272 (PMLR).

Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning , 263–272 (PMLR)

Reference 7

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This paper cites Systems & control letters 61(12):1203–1208.

Statistical and Algorithmic Foundations of Reinforcement Learning Systems & control letters 61(12):1203–1208

Reference 8

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This paper cites Proceedings of the National Academy of Sciences of the United States of America 38(8):716.

Statistical and Algorithmic Foundations of Reinforcement Learning Proceedings of the National Academy of Sciences of the United States of America 38(8):716

Reference 9

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Statistical and Algorithmic Foundations of Reinforcement Learning Unresolved cited work

Reference 10

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This paper cites Mathemat- ical Programming 167(2):235–292.

Statistical and Algorithmic Foundations of Reinforcement Learning Mathemat- ical Programming 167(2):235–292

Reference 11

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This paper cites Management Science 65(2):604–618.

Statistical and Algorithmic Foundations of Reinforcement Learning Management Science 65(2):604–618

Reference 12

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This paper cites International Conference on Artificial Intelligence and Statistics , 2386– 2394 (PMLR).

Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Artificial Intelligence and Statistics , 2386– 2394 (PMLR)

Reference 13

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This paper cites Operations Research 72(5):1906–1927.

Statistical and Algorithmic Foundations of Reinforcement Learning Operations Research 72(5):1906–1927

Reference 14

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Statistical and Algorithmic Foundations of Reinforcement Learning Operations Research 69(3):950–973

Reference 15

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Statistical and Algorithmic Foundations of Reinforcement Learning Mathematics of Operations Research 44(2):565–600

Reference 16

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning , 1056–1066 (PMLR)

Reference 17

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Statistical and Algorithmic Foundations of Reinforcement Learning the method of paired comparisons

Reference 18

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Statistical and Algorithmic Foundations of Reinforcement Learning 2022 IEEE 61st Conference on Decision and Control (CDC) , 2833–2838 (IEEE)

Reference 19

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Statistical and Algorithmic Foundations of Reinforcement Learning Operations Research 70(4):2563– 2578

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Statistical and Algorithmic Foundations of Reinforcement Learning The Eleventh International Conference on Learning Representations

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Statistical and Algorithmic Foundations of Reinforcement Learning The Thirteenth International Conference on Learning Representations

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Statistical and Algorithmic Foundations of Reinforcement Learning Journal of Machine Learning Research 25(4):1–48

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in neural information processing systems 30

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Statistical and Algorithmic Foundations of Reinforcement Learning Unresolved cited work

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Statistical and Algorithmic Foundations of Reinforcement Learning The Annals of Statistics 53(1):426–456

Reference 26

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning , 1042–1051 (PMLR)

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Statistical and Algorithmic Foundations of Reinforcement Learning Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes

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Statistical and Algorithmic Foundations of Reinforcement Learning A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants

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Statistical and Algorithmic Foundations of Reinforcement Learning A Non-Asymptotic Theory of Seminorm Lyapunov Stability: From Deterministic to Stochastic Iterative Algorithms

Reference 30

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in Neural Information Processing Systems 37:1750–1810

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Statistical and Algorithmic Foundations of Reinforcement Learning Thirty-seventh Conference on Neural Informa- tion Processing Systems

Reference 32

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Statistical and Algorithmic Foundations of Reinforcement Learning Algorithmic Learning Theory , 578–598 (PMLR)

Reference 33

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Statistical and Algorithmic Foundations of Reinforcement Learning Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP

Reference 34

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Statistical and Algorithmic Foundations of Reinforcement Learning Bilinear Classes: A Structural Framework for Provable Generalization in RL

Reference 35

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Statistical and Algorithmic Foundations of Reinforcement Learning The Annals of Statistics 49(3):1378–1406

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Statistical and Algorithmic Foundations of Reinforcement Learning Journal of machine learning Research 5(Dec):1–25

Reference 37

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Statistical and Algorithmic Foundations of Reinforcement Learning International conference on machine learning, 1467–1476 (PMLR)

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Statistical and Algorithmic Foundations of Reinforcement Learning The Statistical Complexity of Interactive Decision Making

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Statistical and Algorithmic Foundations of Reinforcement Learning Truncated Variance Reduced Value Iteration

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Statistical and Algorithmic Foundations of Reinforcement Learning Policy learning "without" overlap: Pessimism and generalized empirical Bernstein's inequality

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning , 5055–5064 (PMLR)

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in neural information process- ing systems , 1531–1538

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in neural information processing systems , 996–1002

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Statistical and Algorithmic Foundations of Reinforcement Learning SIAM Journal on Math- ematics of Data Science 3(4):1013–1040

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Statistical and Algorithmic Foundations of Reinforcement Learning Reinforcement learning, 45–73 (Springer)

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Statistical and Algorithmic Foundations of Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

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Statistical and Algorithmic Foundations of Reinforcement Learning Games and economic behavior 10(1):6–38

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Statistical and Algorithmic Foundations of Reinforcement Learning Conference on Learning Theory, 2947–2997 (PMLR)

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Reference 81

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Statistical and Algorithmic Foundations of Reinforcement Learning Operations Research 53(5):780–798

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Statistical and Algorithmic Foundations of Reinforcement Learning (2022) Training language models to follow instructions with human feedback

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Artificial Intelligence and Statistics, 9582–9602 (PMLR)

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Statistical and Algorithmic Foundations of Reinforcement Learning IEEE Transactions on Information Theory 67(1):566–585

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Statistical and Algorithmic Foundations of Reinforcement Learning A Survey on Offline Reinforcement Learning: Taxonomy, Review, and Open Problems

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Reference 87

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Statistical and Algorithmic Foundations of Reinforcement Learning Conference on Learning Theory 3185–3205

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in Neural Information Processing Systems 36

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Statistical and Algorithmic Foundations of Reinforcement Learning IEEE Transactions on Informa- tion Theory 68(12):8156–8196

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Statistical and Algorithmic Foundations of Reinforcement Learning Proceedings of the 35th International Conference on Neural Information Pro- cessing Systems, 15621–15634

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Statistical and Algorithmic Foundations of Reinforcement Learning The Annals of Math- ematical Statistics 400–407

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Statistical and Algorithmic Foundations of Reinforcement Learning The Thirty-eighth Annual Conference on Neural Information Processing Systems

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Statistical and Algorithmic Foundations of Reinforcement Learning The Thirty Seventh Annual Conference on Learning Theory , 4511–4547 (PMLR)

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Reference 95

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Statistical and Algorithmic Foundations of Reinforcement Learning Journal of Machine Learning Research 25(200):1–91

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning (PMLR)

Reference 97

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Statistical and Algorithmic Foundations of Reinforcement Learning International Conference on Machine Learning 19967–20025

Reference 98

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Statistical and Algorithmic Foundations of Reinforcement Learning Advances in Neural Information Processing Systems 36

Reference 99

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Statistical and Algorithmic Foundations of Reinforcement Learning International Confer- ence on Machine Learning , 44909–44959 (PMLR)

Reference 100

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Pith citing papers

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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 and Algorithmic Foundations of Reinforcement Learning

Reference 12

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