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Paper Citation Record · LEDGER

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions

As of 16 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2608.06545.

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

pith.paper-citation-record.v1
2608.06545 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:39:15.637632Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

100 of 300 outbound references displayed

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  • verified fuzzy0
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External citation measurements

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Outbound references

Observation 2ccdd33f-3f04-4beb-a6ae-793c30b353ad · outbound

This paper cites Towards Tight Bounds on the Sample Complexity of Average-Reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Towards Tight Bounds on the Sample Complexity of Average-Reward

Reference 1

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source=arxiv_source observed=2026-08-15T14:39:15.203436Z digest=sha256:1af044e760074e057f329488784560136beebdc23818456f275c1539332580d7

Observation f2cc61b9-093d-4e5a-a0a2-8c15624c0184 · outbound

This paper cites Foundations and Trends in Machine Learning , volume =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Foundations and Trends in Machine Learning , volume =

Reference 2

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Observation 8ea6c8a4-068c-48d2-9b23-c30a2867e586 · outbound

This paper cites Operations Research , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Operations Research , year =

Reference 3

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Observation 18cd24de-c12a-4c63-8b12-ff2875b2223e · outbound

This paper cites Near Sample-Optimal Reduction-Based Policy Learning for Average Reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Near Sample-Optimal Reduction-Based Policy Learning for Average Reward

Reference 4

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Observation 308a30ac-f493-43a3-bd7b-cc343280fed5 · outbound

This paper cites Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward

Reference 5

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Observation 07ceabbc-b080-41b6-adf4-74793e9a4c3b · outbound

This paper cites and Tewari, Ambuj , booktitle =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions and Tewari, Ambuj , booktitle =

Reference 6

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Observation bf3c2cea-2013-4688-bb5a-c88449183c95 · outbound

This paper cites Proceedings of the 35th International Conference on Machine Learning , pages =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Proceedings of the 35th International Conference on Machine Learning , pages =

Reference 7

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Observation a9581ca9-bca9-44e1-b18c-66313c1fc4a2 · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , pages =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Proceedings of the 42nd International Conference on Machine Learning , pages =

Reference 8

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Observation d541f5cd-ef54-46b1-8f06-ffb1343a118f · outbound

This paper cites Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis

Reference 9

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Observation e4a6617e-4655-40c1-86f7-3fdbac929a7e · outbound

This paper cites High-Dimensional Statistics: A Non-Asymptotic Viewpoint , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions High-Dimensional Statistics: A Non-Asymptotic Viewpoint , year =

Reference 10

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Observation 70139650-2f18-4ab0-b2de-5dfa75baba63 · outbound

This paper cites arXiv preprint arXiv:2603.00945 , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions arXiv preprint arXiv:2603.00945 , year =

Reference 11

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Observation 9f37f0ef-f166-4472-8cb7-778a0fd55dfe · outbound

This paper cites Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning , year =

Reference 12

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Observation 3e7d40ca-995e-44ca-9dc9-ed77e017b67b · outbound

This paper cites Efficiently Solving.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Efficiently Solving

Reference 13

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Observation ae41af26-e4af-445c-aae9-695e441f1fc5 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The Twelfth International Conference on Learning Representations , year =

Reference 14

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Observation 76f441f9-afbb-4805-87b0-bc8a917a1e15 · outbound

This paper cites The Plugin Approach for Average-Reward and Discounted.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The Plugin Approach for Average-Reward and Discounted

Reference 15

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Observation 88f0423b-98b0-4821-8345-22477419d669 · outbound

This paper cites Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward

Reference 16

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Observation effe7f4f-ba8d-490d-9f9b-38e263cabdf7 · outbound

This paper cites Sharper Model-Free Reinforcement Learning for Average-Reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Sharper Model-Free Reinforcement Learning for Average-Reward

Reference 17

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Observation bc7cecdf-4059-422f-8f9e-50a6354b90d3 · outbound

This paper cites Journal of Machine Learning Research , volume =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Journal of Machine Learning Research , volume =

Reference 18

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Observation 5866a8ca-c052-40bf-bc7f-c07cdd22a80d · outbound

This paper cites Model-free Reinforcement Learning in Infinite-horizon Average-reward.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Model-free Reinforcement Learning in Infinite-horizon Average-reward

Reference 19

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Observation bda1fb27-dbc1-44e4-8275-9035f35c413e · outbound

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Learning Infinite-horizon Average-reward

Reference 20

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Observation 52a1e67a-ab1f-4cdf-8bfd-44fdaeb2fcea · outbound

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Efficient

Reference 21

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Observation 060f7f15-ac12-4f1e-a64a-c3b93494a9ab · outbound

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally Robust

Reference 22

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This paper cites The International Journal of Robotics Research , volume =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The International Journal of Robotics Research , volume =

Reference 23

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Observation df27e9a6-4869-4efa-af6f-0ab6da554678 · outbound

This paper cites Nature , volume =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Nature , volume =

Reference 24

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Mastering the Game of

Reference 25

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Observation cdd71e41-3f14-437e-a229-b55c90a318e1 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Artificial Intelligence and Statistics , pages =

Reference 26

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions 2020 , organization =

Reference 27

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in Neural Information Processing Systems , volume =

Reference 28

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Artificial Intelligence and Statistics , pages =

Reference 29

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions COLT 2009 - The 22nd Conference on Learning Theory , year =

Reference 30

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Observation caf66f2d-f67c-4a94-88f2-c20bd87974ba · outbound

This paper cites Data-Driven Distributionally Robust Optimization Using the.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Data-Driven Distributionally Robust Optimization Using the

Reference 31

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally robust convex optimization , year =

Reference 32

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Observation 8d85ffe9-de8a-4cd5-99c2-9f2c346e662b · outbound

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally robust optimization and its tractable approximations , year =

Reference 33

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Observation 5066e41a-5384-44dc-aa61-aa46226213b7 · outbound

This paper cites Learning models with uniform performance via distributionally robust optimization , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Learning models with uniform performance via distributionally robust optimization , year =

Reference 34

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Robust Average-Reward

Reference 35

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Observation 13d7ae5b-197e-4f50-99e9-e2f79fbf928d · outbound

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Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions and Prater-Bennette, Ashley and Zou, Shaofeng , booktitle =

Reference 36

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Observation c85eb2ac-fcb5-4b2a-969e-a4e561107ce5 · outbound

This paper cites Toward Theoretical Understandings of Robust.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Toward Theoretical Understandings of Robust

Reference 37

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Observation c9a23339-85dc-413f-8167-7dc904fef751 · outbound

This paper cites Sample Complexity of Variance-Reduced Distributionally Robust.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Sample Complexity of Variance-Reduced Distributionally Robust

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source=arxiv_source observed=2026-08-15T14:39:15.318707Z digest=sha256:a44b5d1d9221dfdbd5cac11c51057c0d1b4ca29cdf39fa511243961944c313dd

Observation 5b71829d-561e-49c5-9191-50ddc86959cf · outbound

This paper cites Near-Optimal Distributionally Robust Reinforcement Learning with General.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Near-Optimal Distributionally Robust Reinforcement Learning with General

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source=arxiv_source observed=2026-08-15T14:39:15.322481Z digest=sha256:9cd59858e20f801232142a53ae74e8f4c04404248b2b871d48850cc7c6ce0d4c

Observation 51e9ba48-0ed9-4ecc-8bc8-9d3e96119b5e · outbound

This paper cites Distributionally robust model-based offline reinforcement learning with near-optimal sample complexity , year =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally robust model-based offline reinforcement learning with near-optimal sample complexity , year =

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source=arxiv_source observed=2026-08-15T14:39:15.325515Z digest=sha256:d125d80c8433efa4688d8551af898731ac3c155792509c59255903a843cb70e0

Observation 82caf014-8a07-4f00-a1b6-b4f5deb0e0e0 · outbound

This paper cites Sample Complexity of Offline Distributionally Robust Linear.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Sample Complexity of Offline Distributionally Robust Linear

Reference 41

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source=arxiv_source observed=2026-08-15T14:39:15.328595Z digest=sha256:f5d50d3800c3bf7b2b0be6d9ec15be6acfc0113ae1095b9540847235d334cd11

Observation 0277484c-a2c1-4750-8320-96faf0343c2f · outbound

This paper cites 1994 , publisher =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions 1994 , publisher =

Reference 42

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source=arxiv_source observed=2026-08-15T14:39:15.331697Z digest=sha256:ce1c70cdc90461dd82b9d50b4baa5ea4f0db3f498884d9b8be8707df1314f44a

Observation 0acdd3e8-5b79-46af-849f-79700514230d · outbound

This paper cites Tsybakov , publisher =.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Tsybakov , publisher =

Reference 43

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source=arxiv_source observed=2026-08-15T14:39:15.334697Z digest=sha256:e49fe67a21012716df9b2e016fa1c8a6ebcb027cb02ba06a6f42bd32a8e45979

Observation f9b615a3-36c1-47b2-a5fc-34953045dd77 · outbound

This paper cites Machine learning , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Machine learning , volume=

Reference 44

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source=arxiv_source observed=2026-08-15T14:39:15.338841Z digest=sha256:591ddb42628037dc4e406e2fbc14c54dee698bb356907b626fb126d7c374c8d0

Observation d42131d3-33cc-4460-a376-4f7a909dfe1e · outbound

This paper cites International Conference on Machine Learning , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Machine Learning , pages=

Reference 45

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source=arxiv_source observed=2026-08-15T14:39:15.341917Z digest=sha256:88db3afd1e99d5a335c575e9388473667d27ec0ba9efb22dda1acf1e43b4c850

Observation 219b76fe-3d4c-467a-afbe-9f27746d6e13 · outbound

This paper cites Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning

Reference 46

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source=arxiv_source observed=2026-08-15T14:39:15.344469Z digest=sha256:84f88bddb9016b2bd40e37f9de6f8429d0b03a9a5e9e8292a97ddb9faa4e9c2c

Observation d613f426-39b7-478e-b447-630fadb22f2e · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Forty-second International Conference on Machine Learning , year=

Reference 47

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source=arxiv_source observed=2026-08-15T14:39:15.347703Z digest=sha256:aa18ddd3780f7f2f9e60228bcd0ea73f91a165e036af4d909715b37ed096f552

Observation 9babee25-36ec-45a5-8cd0-f2e18149d86e · outbound

This paper cites The blessing of heterogeneity in federated.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The blessing of heterogeneity in federated

Reference 48

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source=arxiv_source observed=2026-08-15T14:39:15.350738Z digest=sha256:398cbf07f2a48ba5ec87b583d5a2d629b3b7793c15deeb220eac866afddde523

Observation 3d5003de-2530-4f7f-a5e2-59e8f1b38eed · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in Neural Information Processing Systems , volume=

Reference 49

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source=arxiv_source observed=2026-08-15T14:39:15.353842Z digest=sha256:ffe77f89a4396f857d85a1f109abb94dd6f4b74ef5cba136b932488e266a8a3c

Observation 3b7dc32c-427a-4975-b155-89302f03eebd · outbound

This paper cites Thirty-seventh Conference on Neural Information Processing Systems , year=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Thirty-seventh Conference on Neural Information Processing Systems , year=

Reference 50

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source=arxiv_source observed=2026-08-15T14:39:15.356422Z digest=sha256:041fb0b614987f78ce58bf76163b5424f4391e8e06591f23f2bbb7acd6f4b80b

Observation d03d0526-5a80-4b81-b762-847536a57436 · outbound

This paper cites Operations research , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Operations research , volume=

Reference 51

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source=arxiv_source observed=2026-08-15T14:39:15.359852Z digest=sha256:b53ff8ecc2f0299e797e463baa28ab08d1584e30144decf2655f63fa0e14d552

Observation a3b7a8dd-08e4-44e2-9442-3a14b31ff866 · outbound

This paper cites Robust control of.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Robust control of

Reference 52

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source=arxiv_source observed=2026-08-15T14:39:15.486678Z digest=sha256:2852eb564fe0ab5591e9463a1ad3ec67003dd50626f8f9f683b8881ac92d01dd

Observation cdfc98d3-e4d7-4f31-bdef-0eeadf2f775e · outbound

This paper cites $Q$-learning with Logarithmic Regret.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions $Q$-learning with Logarithmic Regret

Reference 53

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local_arxiv, observed 2026-08-15T14:39:17.048249Z

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source=arxiv_source observed=2026-08-15T14:39:15.493614Z digest=sha256:12b456a8bca1e3bd127b4d10bdc634f92a71541fae02833f5559e043892c0f3d

Observation 791b6d3f-07a0-4b23-b368-86e548e84c4f · outbound

This paper cites Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning

Reference 54

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source=arxiv_source observed=2026-08-15T14:39:15.496949Z digest=sha256:c2b0cb4dec13b0be87f9b28fe40dc3c4baa09fd516fbc4ca9790f6884b105593

Observation 78457264-6cba-4039-9fd9-2f848b71ca06 · outbound

This paper cites Advances in neural information processing systems , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in neural information processing systems , pages=

Reference 55

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source=arxiv_source observed=2026-08-15T14:39:15.500102Z digest=sha256:316665bdcc91f93923cac2b6a85d2c7a1d512c8dadc02589d0020e149deaf99d

Observation 4d4d9a1c-2280-4df3-8905-23cfc31a8ac3 · outbound

This paper cites Complete Dictionary Learning via $\ell_p$-norm Maximization.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Complete Dictionary Learning via $\ell_p$-norm Maximization

Reference 56

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source=arxiv_source observed=2026-08-15T14:39:15.503037Z digest=sha256:eb5b27136c46c6160bb45e00dce283b88ca74aad048b1ce972d7d4ed73d8b098

Observation 4c2ba3de-423a-48a3-993f-8e7b0fc6da5f · outbound

This paper cites Journal of Applied Probability , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Journal of Applied Probability , volume=

Reference 57

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source=arxiv_source observed=2026-08-15T14:39:15.506776Z digest=sha256:21cf78c018af48e90b45ec1deb238dfe27e5303adc95aa8a2ec9ef9724262e3b

Observation d88536b2-f16f-4da6-955f-bbe6e9d0198e · outbound

This paper cites Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms

Reference 58

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source=arxiv_source observed=2026-08-15T14:39:15.509987Z digest=sha256:8685fd8c413f5f078f89aede400b3bf835e684982b934fea8d92235501206c12

Observation b285e844-8231-4ac4-b382-a11c23509a4c · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in Neural Information Processing Systems , volume=

Reference 59

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source=arxiv_source observed=2026-08-15T14:39:15.513098Z digest=sha256:e4858c7e89ec9209486f855c62b1678073e236c4e2cee5d6cae6876fdf294dcf

Observation a2746f34-f148-4e9d-b074-5d3f586fae8e · outbound

This paper cites On the Global Convergence Rates of Softmax Policy Gradient Methods.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions On the Global Convergence Rates of Softmax Policy Gradient Methods

Reference 60

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source=arxiv_source observed=2026-08-15T14:39:15.516180Z digest=sha256:d7d2a5a92827ef98f909e8c91fe4de2be5088f82a7a3360d89a4aa8bafceb140

Observation 9bfa37da-e391-4468-aad1-830e70ba60a6 · outbound

This paper cites ICML , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions ICML , volume=

Reference 61

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source=arxiv_source observed=2026-08-15T14:39:15.519221Z digest=sha256:7a177ca98efc988f15f2047e6b9ec61758217902c93da4c8a4aba243bce3abca

Observation 24b203a2-f37d-4dad-9454-be3634036b70 · outbound

This paper cites Optimality and approximation with policy gradient methods in.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Optimality and approximation with policy gradient methods in

Reference 62

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source=arxiv_source observed=2026-08-15T14:39:15.521951Z digest=sha256:2f0a208e5ade97b8c27025e48ff8e481d39d08336e331e16a9f744685852fb48

Observation 4619700e-2526-4d70-b16f-2937434744ee · outbound

This paper cites Advances in neural information processing systems , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in neural information processing systems , volume=

Reference 63

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source=arxiv_source observed=2026-08-15T14:39:15.524694Z digest=sha256:e59743e06379cbc50b3ea7bc93663f22884e32eab057c6b42802343ec7ac8821

Observation 6acaff08-1837-4d96-8ec8-579d4069fbd3 · outbound

This paper cites Advances in neural information processing systems , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in neural information processing systems , pages=

Reference 64

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source=arxiv_source observed=2026-08-15T14:39:15.527449Z digest=sha256:b60cc09cee5359ac38d245faece8f716a0493b9a82462809a627104a53299bb9

Observation bf8226aa-05b0-4c66-bf10-6907e51e48cc · outbound

This paper cites an unresolved cited work.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Unresolved cited work

Reference 65

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source=arxiv_source observed=2026-08-15T14:39:15.530633Z digest=sha256:b95a8ad9b4a2959c9a4fb41bf7462aefbd8390cde9ca63b573fcd8412d4ca26e

Observation bb02d565-1b38-4e88-ba39-9677c0ba4def · outbound

This paper cites Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

Reference 66

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local_arxiv, observed 2026-08-15T14:39:16.986137Z

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source=arxiv_source observed=2026-08-15T14:39:15.533537Z digest=sha256:0d1b30f553f2880c652242f05cdaf951ae812fe8ea12fe03b77fceca591cb3c9

Observation 41ab3e61-0120-460f-adce-2841f65c14c5 · outbound

This paper cites Probability Theory and Related Fields , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Probability Theory and Related Fields , volume=

Reference 67

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source=arxiv_source observed=2026-08-15T14:39:15.536769Z digest=sha256:05adeb1e7a24ce8e7ddea279e24e5d9d2111abda26eeca77d92ce27527fa249b

Observation ad91d121-3c2d-4722-8a4f-b3625fa945fd · outbound

This paper cites Proceedings of the 27th international conference on international conference on machine learning , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Proceedings of the 27th international conference on international conference on machine learning , pages=

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source=arxiv_source observed=2026-08-15T14:39:15.540035Z digest=sha256:88b63b301bef8371113c55ff026cdd51bb8d09607377a49e950b3956b7d792eb

Observation 61a978c1-dc40-42d6-8a93-e2f6ea1fb7fa · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Learning Representations (ICLR) , year=

Reference 69

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source=arxiv_source observed=2026-08-15T14:39:15.543051Z digest=sha256:ceeef21d3d9a226b675a97033848a18409fcb30c87e62103a20b22f08e777c38

Observation 5a63e9ef-e709-4519-a2f2-b938816c1d4e · outbound

This paper cites Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and Thresholds

Reference 70

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source=arxiv_source observed=2026-08-15T14:39:15.545887Z digest=sha256:f6b69584b7ac56ed19dc5d5b53125db076b03470c0b9a303378dd57b1c2c8abb

Observation 835631c6-af5a-4d43-8270-834dab3ff1ba · outbound

This paper cites Ada-LISTA: Learned Solvers Adaptive to Varying Models.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Ada-LISTA: Learned Solvers Adaptive to Varying Models

Reference 71

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source=arxiv_source observed=2026-08-15T14:39:15.548922Z digest=sha256:37675dd6a4edfb76d260b26c76811459a06276694213e4a5e585e8222382591d

Observation caac32fe-da59-4a36-a272-c0efd64b4a3c · outbound

This paper cites Understanding Trainable Sparse Coding via Matrix Factorization.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Understanding Trainable Sparse Coding via Matrix Factorization

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source=arxiv_source observed=2026-08-15T14:39:15.552169Z digest=sha256:5fc22c7f693b60f829d22ceade1353631e275859bb86c03d87d1a075f4ad5883

Observation 14528f54-1f2e-4b30-ab9b-7c9c74523b67 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Artificial Intelligence and Statistics , pages=

Reference 73

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source=arxiv_source observed=2026-08-15T14:39:15.555278Z digest=sha256:e92eb34aed337aebf97fe9e3ebe301530056d9f7bfa718afcb09210b97d1c4bc

Observation bc2f6af1-29a9-45fd-b665-3ca9bf0dc9fe · outbound

This paper cites Mathematics of Operations Research , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Mathematics of Operations Research , volume=

Reference 74

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source=arxiv_source observed=2026-08-15T14:39:15.558053Z digest=sha256:c0d72aceadf4d12668d7e3245ef126e5bc5a7e31fd33a4676c192bc59c77068c

Observation 3dde4795-b613-4951-b572-7d0e891208ea · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in Neural Information Processing Systems , volume=

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source=arxiv_source observed=2026-08-15T14:39:15.560606Z digest=sha256:3e7a22b1951bcccf5c7e51c036c46e421b02f8efe8b66e20daf797af798709f0

Observation 0e6eac17-e3d8-47c5-96cb-ecc2c259c858 · outbound

This paper cites Twice regularized.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Twice regularized

Reference 76

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source=arxiv_source observed=2026-08-15T14:39:15.563461Z digest=sha256:0d36edd32c6634260f7367ab6db6137b23a12a2dce92650eb911cf79c4414355

Observation 5e06f2a4-1d0e-41aa-b21b-c3ef8b779bcb · outbound

This paper cites International Conference on Machine Learning , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Machine Learning , pages=

Reference 77

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source=arxiv_source observed=2026-08-15T14:39:15.566048Z digest=sha256:75ae9b420fc1e00b66e09f613c65e8fccff354730ecf0bd8680cbcbdf70e4530

Observation 1ce8b195-a019-46e1-a093-05fdf0f79678 · outbound

This paper cites A Review of Off-Policy Evaluation in Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions A Review of Off-Policy Evaluation in Reinforcement Learning

Reference 78

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source=arxiv_source observed=2026-08-15T14:39:15.568605Z digest=sha256:5a83d776a295eca2a4e4adb63cc196b41f2097c070d4fe78c0694bb76d875872

Observation 73c7a7ad-9d56-440f-a888-20da053818af · outbound

This paper cites International Conference on Machine Learning , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions International Conference on Machine Learning , pages=

Reference 79

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source=arxiv_source observed=2026-08-15T14:39:15.571404Z digest=sha256:995be162da75fb54abe70ad826439991844e7fdffcd4c6685d3e9f972dccae43

Observation 1fd2fac0-ba16-429b-aad4-5d1ca99d20bc · outbound

This paper cites Distributionally Robust Optimization: A Review.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally Robust Optimization: A Review

Reference 80

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source=arxiv_source observed=2026-08-15T14:39:15.574358Z digest=sha256:60f4cd006301dd20b91dd343d53bb8a70edc6b2af4210b1af0e31768a7a0b6d5

Observation 95b26c2f-0f01-4095-a4a2-0ece99f3e556 · outbound

This paper cites Finite-sample guarantees for.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Finite-sample guarantees for

Reference 81

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source=arxiv_source observed=2026-08-15T14:39:15.578729Z digest=sha256:aebe3228ce622648a1f384a6ef242b42eeb65687b9bfb42888927a01f914328c

Observation 11359dc3-2b4b-499a-9887-c87535093a98 · outbound

This paper cites Certifying Model Accuracy under Distribution Shifts.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Certifying Model Accuracy under Distribution Shifts

Reference 82

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source=arxiv_source observed=2026-08-15T14:39:15.581826Z digest=sha256:955b628f8b34230d591d8c21bcd47bca96f344d544f51d7e29f1c74da978e0a3

Observation a76b1b01-4c57-423d-a0bf-bc2a6f1facfb · outbound

This paper cites Advances in neural information processing systems , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Advances in neural information processing systems , volume=

Reference 83

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source=arxiv_source observed=2026-08-15T14:39:15.585147Z digest=sha256:008abf33a5e446b0d8267b5bcb8d94e184cd2b20d67a9f61ceb01914a1c00f97

Observation 3fd88426-9fe4-4008-b4d0-9a108e0bdd80 · outbound

This paper cites Settling the Sample Complexity of Model-Based Offline Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Settling the Sample Complexity of Model-Based Offline Reinforcement Learning

Reference 84

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local_arxiv, observed 2026-08-15T14:39:16.893053Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T14:39:15.588609Z digest=sha256:01f6627226b80ca906eb8b496534624ff87d44e85eb8545c6d40e6452e2adf15

Observation d72da13f-f3f1-4232-974a-19cff24db1e6 · outbound

This paper cites Available at Optimization Online , pages=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Available at Optimization Online , pages=

Reference 85

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source=arxiv_source observed=2026-08-15T14:39:15.591949Z digest=sha256:bb770f8c2e44864a65b840ccf065f8690a89cb4fc555b350cc9fef3503317cac

Observation 81a5dc8b-44de-43f4-97e9-b1e3e9a9078a · outbound

This paper cites Pessimistic.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Pessimistic

Reference 86

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source=arxiv_source observed=2026-08-15T14:39:15.594947Z digest=sha256:09f78c45904cd5a21ae073823208224df46f354672171f1299324b421e9f1c76

Observation 1ca62b82-0e54-4ad5-94c9-e6599cd5f221 · outbound

This paper cites The Bell system technical journal , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The Bell system technical journal , volume=

Reference 87

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source=arxiv_source observed=2026-08-15T14:39:15.597974Z digest=sha256:e5f74990e1ce59b1e32232e3fb8d7775865bfe9d71b6ea0c13b87be40d712af8

Observation 3bf77a69-8377-415e-9085-5610c6dd79f5 · outbound

This paper cites The mathematics of data , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The mathematics of data , volume=

Reference 88

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source=arxiv_source observed=2026-08-15T14:39:15.600564Z digest=sha256:4265a773e8d7efd03414f306ff9fdaa95b21cfc411aa2c0c7804bc358c6937f7

Observation 0e2948c7-0976-4bd5-a85a-bce669fd91ee · outbound

This paper cites The Journal of finance , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions The Journal of finance , volume=

Reference 89

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source=arxiv_source observed=2026-08-15T14:39:15.603762Z digest=sha256:f9d65567364c79c73ce91d1678c810000bb94859f8037a34282fdbb3ba84d50f

Observation a06183ee-4d5e-455b-a185-f794e2047b6b · outbound

This paper cites , author=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions , author=

Reference 90

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source=arxiv_source observed=2026-08-15T14:39:15.606758Z digest=sha256:6af65c95de13d2f7a06531cb61ceabe7b78d8dd2b20e20c14467f206ab40c6bd

Observation 47828712-199e-4990-a716-666c81d0da09 · outbound

This paper cites Mathematical Programming , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Mathematical Programming , volume=

Reference 91

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source=arxiv_source observed=2026-08-15T14:39:15.609707Z digest=sha256:af93982631981873f5fd777eea9eedfa2f8fb1cbfddbb2a361d52a1b19c5b495

Observation df1e378e-fe72-4bd8-b904-22dd29d668a4 · outbound

This paper cites Mathematics of Operations Research , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Mathematics of Operations Research , volume=

Reference 92

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source=arxiv_source observed=2026-08-15T14:39:15.613255Z digest=sha256:e08b993fc27b9ab73d599b4e29b9efcc69c9561210a70791037a2a7c6cb4fef6

Observation b86932a2-17df-4343-9aa1-13f973b37687 · outbound

This paper cites Robust control of uncertain.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Robust control of uncertain

Reference 93

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source=arxiv_source observed=2026-08-15T14:39:15.616496Z digest=sha256:ec0a3adb43f487db406b8fe8cb42afcc8154b6b8f6df8aab1855fef4f83579e2

Observation a521443e-c233-48e4-876b-650f335feb2a · outbound

This paper cites an unresolved cited work.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Unresolved cited work

Reference 94

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source=arxiv_source observed=2026-08-15T14:39:15.619844Z digest=sha256:84c9e86c1ebda4567ef6e71efbc51c96f0d97e969f046a36e14ce834ec280dea

Observation d86bc39b-ddcb-44e3-8a07-023b3e422c4d · outbound

This paper cites INFORMS Journal on Computing , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions INFORMS Journal on Computing , volume=

Reference 95

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source=arxiv_source observed=2026-08-15T14:39:15.622784Z digest=sha256:3b842d9b2c227b17cb883486b89fd3f89aee978691900ad41caa51758751b0b2

Observation c290e883-4b9c-42ec-b04f-c5ed1283589c · outbound

This paper cites an unresolved cited work.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Unresolved cited work

Reference 96

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source=arxiv_source observed=2026-08-15T14:39:15.625757Z digest=sha256:e9f47e81e4bd7ebb412e98684d6a5b28368532109dd7d5ae9973bdbec8e5c6c1

Observation 29f6aba9-0e16-4f56-af81-020f27f8653c · outbound

This paper cites Distributionally Robust Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributionally Robust Reinforcement Learning

Reference 97

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source=arxiv_source observed=2026-08-15T14:39:15.628743Z digest=sha256:040a366b062855bda73d724f9687c7dce5701fdd2b471db855dd7bf529e7a8e1

Observation e8b0c55a-7f0a-445a-a4ca-a48965dd18c3 · outbound

This paper cites Journal of Machine Learning Research , volume=.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Journal of Machine Learning Research , volume=

Reference 98

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source=arxiv_source observed=2026-08-15T14:39:15.631794Z digest=sha256:862a3e672960803763fd62c25bbe3f07ee096e91fb45524b23064ec3a0f9ff83

Observation a6bed617-be62-448b-b66d-d30b9ee729a8 · outbound

This paper cites an unresolved cited work.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Unresolved cited work

Reference 99

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source=arxiv_source observed=2026-08-15T14:39:15.634562Z digest=sha256:10c5e4a55376f90a21f92a285d5ecc848ae6b14b76fc0cefd7e996bb552fe777

Observation 88f1c433-0416-48a4-bdf1-f5f8f2a8cef7 · outbound

This paper cites Distributional Robustness and Regularization in Reinforcement Learning.

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions Distributional Robustness and Regularization in Reinforcement Learning

Reference 100

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source=arxiv_source observed=2026-08-15T14:39:15.637632Z digest=sha256:cfa2982a8cdc19180d0044757f0ff5c314ff23c94672575b3bc582757e1d5751

Pith citing papers

No inbound Pith citation observations are available.