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Paper Citation Record · LEDGER

Operator Splitting for Convex Constrained Markov Decision Processes

As of 14 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2412.14002.

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

pith.paper-citation-record.v1
2412.14002 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:40:45.727688Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

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

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T01:40:08.230114Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T12:55:44.116744Z

Reference resolution

62 of 62 outbound references displayed

  • verified exact4
  • verified fuzzy42
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d5debb6-f0c9-42d9-8d71-e9b5c137e1ba · outbound

This paper cites Mastering the game of go without human knowledge,.

Operator Splitting for Convex Constrained Markov Decision Processes Mastering the game of go without human knowledge,

Reference 1

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raw_fallback, observed 2026-08-11T12:40:46.474791Z

Source-reported events for the cited work

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

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Observation a14a017c-7b4c-46bb-93e6-842395d858bc · outbound

This paper cites Magnetic control of tokamak plasmas through deep reinforcement learning,.

Operator Splitting for Convex Constrained Markov Decision Processes Magnetic control of tokamak plasmas through deep reinforcement learning,

Reference 2

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raw_fallback, observed 2026-08-11T12:40:46.463803Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.527737Z digest=sha256:756e0ee8de10af72a30f5d506914faf5a13040c8e27f81781a1705f7662dfeaf

Observation fc2e3662-6eba-4b80-8a36-fd86e8f01db8 · outbound

This paper cites an unresolved cited work.

Operator Splitting for Convex Constrained Markov Decision Processes Unresolved cited work

Reference 3

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no resolver link, observed 2026-08-11T12:40:45.531734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.531734Z digest=sha256:1dce6545699c09388036026d6ecf3541ea74303202d9e564a161d5e1dd9a1f2a

Observation d5ac92ef-5561-4ba3-9ad0-9402d472a519 · outbound

This paper cites Altman, Constrained Markov decision processes.

Operator Splitting for Convex Constrained Markov Decision Processes Altman, Constrained Markov decision processes

Reference 4

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no resolver link, observed 2026-08-11T12:40:45.535342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.535342Z digest=sha256:1e5fabfcac45419415a2166147f521fadb7c4ba74ad12435e013408d8d5d2d43

Observation 5a515a8e-f66a-489c-a58b-7e289c4e5f3f · outbound

This paper cites Policy gradients with variance related risk criteria,.

Operator Splitting for Convex Constrained Markov Decision Processes Policy gradients with variance related risk criteria,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.438344Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.539032Z digest=sha256:3ad497366959f7b788d86d178211e7ffcaa866396046bf24ce75c3e4d6241c86

Observation 9ec6acb3-8b02-4766-91c3-e51e28f664db · outbound

This paper cites Risk-constrained reinforcement learning with percentile risk criteria,.

Operator Splitting for Convex Constrained Markov Decision Processes Risk-constrained reinforcement learning with percentile risk criteria,

Reference 6

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raw_fallback, observed 2026-08-11T12:40:46.426469Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.542889Z digest=sha256:9dfd03df3574970fd8da23cebd29566f9fd15dd3b8cbfe6453507aa192b561d2

Observation ee91af8a-5923-494f-a011-6aca5f6ab9d7 · outbound

This paper cites Control and optimization meet the smart power grid: Scheduling of power demands for optimal energy management,.

Operator Splitting for Convex Constrained Markov Decision Processes Control and optimization meet the smart power grid: Scheduling of power demands for optimal energy management,

Reference 7

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raw_fallback, observed 2026-08-11T12:40:46.416377Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.546898Z digest=sha256:84beb8903a20c2d4c930c5b138df7ae0df8010f72b9972a5bd97f8e26f636361

Observation 542b87d3-b08d-435d-be6e-0e07797a0d49 · outbound

This paper cites Constrained policy optimization,.

Operator Splitting for Convex Constrained Markov Decision Processes Constrained policy optimization,

Reference 8

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.550549Z digest=sha256:12d3e4ad4e02e12d4e256b881428855f0c30850d91e5d4c578d03a69e48fcb3a

Observation 45b38f5c-3b29-440f-81cb-573b57a0950d · outbound

This paper cites Dynamic programming equations for dis- counted constrained stochastic control,.

Operator Splitting for Convex Constrained Markov Decision Processes Dynamic programming equations for dis- counted constrained stochastic control,

Reference 9

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raw_fallback, observed 2026-08-11T12:40:46.396802Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.553944Z digest=sha256:daf508931ff6581f8f26330a6db6376e84ecd629e4648056fe5aac8c852f9caa

Observation ad5d1b4d-e489-46fd-b2bf-0ace75ad2016 · outbound

This paper cites Dynamic programming in constrained Markov decision processes,.

Operator Splitting for Convex Constrained Markov Decision Processes Dynamic programming in constrained Markov decision processes,

Reference 10

Resolution
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raw_fallback, observed 2026-08-11T12:40:46.387474Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.557316Z digest=sha256:9731e8c6376dd8a84377543aac8d2a3868e967022ca5899ca1a12cfb40f1e996

Observation cd8afd8c-185d-45f4-bb8d-cdd29e24ae5f · outbound

This paper cites A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes.

Operator Splitting for Convex Constrained Markov Decision Processes A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes

Reference 11

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local_arxiv, observed 2026-08-11T12:40:45.942537Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.560934Z digest=sha256:43a7ed83c7a685a8c531a8cba75ff63ae7aecbad2b7a5e30ae6d574b352f321e

Observation 81bb3222-c4a7-4975-9bfa-60d1a820a59d · outbound

This paper cites Natural policy gradient primal-dual method for constrained Markov decision processes,.

Operator Splitting for Convex Constrained Markov Decision Processes Natural policy gradient primal-dual method for constrained Markov decision processes,

Reference 12

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raw_fallback, observed 2026-08-11T12:40:46.376767Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.564782Z digest=sha256:a808d202f628b0c950ee028f9b21691a3e234883a9e1728ab6c8a4af7cb02fca

Observation a42db668-8b00-4eca-88ab-0631211d5210 · outbound

This paper cites Learning policies with zero or bounded constraint violation for constrained MDPs,.

Operator Splitting for Convex Constrained Markov Decision Processes Learning policies with zero or bounded constraint violation for constrained MDPs,

Reference 13

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.568209Z digest=sha256:bf5a4829cb5f30f97cf6c688a9607c0de95ab81a98dda248e0a2098d0553af0e

Observation e5e4fd73-681f-4d25-8067-da8a5f2ce359 · outbound

This paper cites State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards.

Operator Splitting for Convex Constrained Markov Decision Processes State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards

Reference 14

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local_arxiv, observed 2026-08-11T12:40:45.928287Z

Source-reported events for the cited work

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

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Observation 059a8990-aadc-44e1-b9e0-bbe49e2e94f9 · outbound

This paper cites Constrained MDPs and the reward hypothesis.

Operator Splitting for Convex Constrained Markov Decision Processes Constrained MDPs and the reward hypothesis

Reference 15

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Source-reported events for the cited work

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

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Observation dc886c82-2731-4f9d-a3a9-9c3e88d9d4ec · outbound

This paper cites Two “well-known.

Operator Splitting for Convex Constrained Markov Decision Processes Two “well-known

Reference 16

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.576948Z digest=sha256:9f2eba7ed314131ad9a2f511ea84c5557cd0471bb0ec8bbd9a469cddc7abb0c7

Observation 94358415-df0b-4c2c-8470-c8a9c5a99ca8 · outbound

This paper cites Algorithm for constrained Markov decision process with linear convergence,.

Operator Splitting for Convex Constrained Markov Decision Processes Algorithm for constrained Markov decision process with linear convergence,

Reference 17

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.579723Z digest=sha256:e876093bd47d63e0a472070b770d9da9ba77a9cc70e1a21fa461f3515210dbfa

Observation df37e178-a510-4759-9e23-c8ca8325bc49 · outbound

This paper cites Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process.

Operator Splitting for Convex Constrained Markov Decision Processes Faster Algorithm and Sharper Analysis for Constrained Markov Decision Process

Reference 18

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local_arxiv, observed 2026-08-11T12:40:45.912662Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.582528Z digest=sha256:2c9ed38b046ac84aa8a6ed3662f2f2dc049cf5d89bc8df72963c771b3a233fee

Observation 436de9d0-9ff3-4e8f-8b7a-e28e86f689d4 · outbound

This paper cites Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes.

Operator Splitting for Convex Constrained Markov Decision Processes Cancellation-Free Regret Bounds for Lagrangian Approaches in Constrained Markov Decision Processes

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.585747Z digest=sha256:d4f920b21e274daeea557871ac87259815188b98a4e87cc514b4bda4dbc79215

Observation e7dc5fbf-0b77-45e9-bc34-8fb93dbf9c2d · outbound

This paper cites Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs.

Operator Splitting for Convex Constrained Markov Decision Processes Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs

Reference 20

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no resolver link, observed 2026-08-11T12:40:45.589096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.589096Z digest=sha256:385dbb6a0495ec1d428de1e21928c5c5cda3a048154747a996465618d4e88d53

Observation d9b00ec9-7e4a-45d9-b6c9-35dac966afef · outbound

This paper cites Reload: Reinforcement learning with optimistic ascent- descent for last-iterate convergence in constrained MDPs,.

Operator Splitting for Convex Constrained Markov Decision Processes Reload: Reinforcement learning with optimistic ascent- descent for last-iterate convergence in constrained MDPs,

Reference 21

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.592853Z digest=sha256:e4669e7ded52d95e15fc96d41d05b5e5747f652d983da4d35e13dfba4ea9ec32

Observation 15e44324-8a48-4e21-aec3-1d4ff6d76fea · outbound

This paper cites Ipo: Interior-point policy optimization under constraints,.

Operator Splitting for Convex Constrained Markov Decision Processes Ipo: Interior-point policy optimization under constraints,

Reference 22

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raw_fallback, observed 2026-08-11T12:40:46.313087Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.596272Z digest=sha256:2586cd8c682109a32cb983b2c072b18764bc305365a98840331da990d109def0

Observation d9ca5f64-4792-4ad5-8b81-cca65e75d970 · outbound

This paper cites Projection-Based Constrained Policy Optimization.

Operator Splitting for Convex Constrained Markov Decision Processes Projection-Based Constrained Policy Optimization

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.599554Z digest=sha256:10b4d8c611dc8ef3610e59808d6c54fb877010607a122883109f350c034ac6b1

Observation 0bc2fc3e-f15d-42a0-b7ac-9ed2ce28805e · outbound

This paper cites Reward is enough for convex MDPs,.

Operator Splitting for Convex Constrained Markov Decision Processes Reward is enough for convex MDPs,

Reference 24

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raw_fallback, observed 2026-08-11T12:40:46.302622Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.604198Z digest=sha256:52421f077e96ac85ece8826501dbd27b4461fd3b3818ffc4d5c6c8166b0ea045

Observation 3b81aac5-0a43-47d3-8586-bddbc21ce90a · outbound

This paper cites Apprenticeship learning via inverse reinforce- ment learning,.

Operator Splitting for Convex Constrained Markov Decision Processes Apprenticeship learning via inverse reinforce- ment learning,

Reference 25

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raw_fallback, observed 2026-08-11T12:40:46.292322Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.607868Z digest=sha256:674b6e410eed00c802645e4f1de7487b361e0fb6affd7f740513071d8d1b2c19

Observation 41a27b59-5d10-424e-9af1-3f570162db0b · outbound

This paper cites Provably efficient maximum entropy exploration,.

Operator Splitting for Convex Constrained Markov Decision Processes Provably efficient maximum entropy exploration,

Reference 26

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raw_fallback, observed 2026-08-11T12:40:46.281858Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.611007Z digest=sha256:749a43e2c85cd2678671ed45957b156ef068b1c8f88bf1b92a248b18cd717124

Observation b9945c27-18a9-4bb5-8a98-148d484fa784 · outbound

This paper cites Diversity is All You Need: Learning Skills without a Reward Function.

Operator Splitting for Convex Constrained Markov Decision Processes Diversity is All You Need: Learning Skills without a Reward Function

Reference 27

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unresolved
no resolver link, observed 2026-08-11T12:40:45.614529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.614529Z digest=sha256:5d4bdcfbb5627afc31f8fcb0cc734ca6f2e1216ef9be3ce62dfb4ce8e9cf7dc2

Observation a405dd85-26bc-424e-9b46-9cece872a9ad · outbound

This paper cites Policy-based primal-dual methods for convex constrained Markov decision processes,.

Operator Splitting for Convex Constrained Markov Decision Processes Policy-based primal-dual methods for convex constrained Markov decision processes,

Reference 28

Resolution
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raw_fallback, observed 2026-08-11T12:40:46.271500Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.618422Z digest=sha256:33d1f78e61094664ce892d4a268b7d60eba0d5990ec0b839e3de69b81c1044e1

Observation 5d238fcc-519d-47b8-97fe-741bdfe0b226 · outbound

This paper cites Variational policy gradient method for reinforcement learning with general utilities,.

Operator Splitting for Convex Constrained Markov Decision Processes Variational policy gradient method for reinforcement learning with general utilities,

Reference 29

Resolution
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raw_fallback, observed 2026-08-11T12:40:46.260720Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.621795Z digest=sha256:4892e9b0e11a1ce1fcc4e187a61b40dc17f05ef6c7dbf52563355a59b292f3c8

Observation 5c4a64fb-80a3-4e21-babd-fb34144bf916 · outbound

This paper cites Reinforcement learning with convex constraints,.

Operator Splitting for Convex Constrained Markov Decision Processes Reinforcement learning with convex constraints,

Reference 30

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raw_fallback, observed 2026-08-11T12:40:46.249377Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.625100Z digest=sha256:71bc20c6f1010c04842ee8b2e4ceb3610aa7000fa61ab284066cd5726fc773d1

Observation 6452146a-e617-4068-b5a7-af6bf91dbf54 · outbound

This paper cites A simple reward-free approach to constrained reinforcement learning,.

Operator Splitting for Convex Constrained Markov Decision Processes A simple reward-free approach to constrained reinforcement learning,

Reference 31

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raw_fallback, observed 2026-08-11T12:40:46.238752Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.628643Z digest=sha256:5b4c377e05ed28e57ecd3c78f4b76a5cd2ffb937d9e1f301fc65cf1b26f83e1d

Observation 002b4718-6274-4d5d-8a35-5130c8ea7d9c · outbound

This paper cites Bauschke and P.

Operator Splitting for Convex Constrained Markov Decision Processes Bauschke and P

Reference 32

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raw_fallback, observed 2026-08-11T12:40:46.227584Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.632070Z digest=sha256:8e3051f25c6357fa0948a5f8e9894c8996cd3725e656b5d7ce049539db82175b

Observation aae25587-1f49-4ccd-bdf5-ae98d45aed63 · outbound

This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers,.

Operator Splitting for Convex Constrained Markov Decision Processes Distributed optimization and statistical learning via the alternating direction method of multipliers,

Reference 33

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no resolver link, observed 2026-08-11T12:40:45.635420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.635420Z digest=sha256:7101cf47ff697dc29262d5180c0c8a6781e4feb5e0547a63a01ce102a9243a64

Observation 8694d196-c0b1-433a-91ec-0f717a1e6517 · outbound

This paper cites A note on the equivalence of operator splitting methods,.

Operator Splitting for Convex Constrained Markov Decision Processes A note on the equivalence of operator splitting methods,

Reference 34

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raw_fallback, observed 2026-08-11T12:40:46.210336Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.638587Z digest=sha256:edde6900865fefa321f568fde2c86fdaf1e6845fd9bb225ba94f2a5a5929f6b1

Observation 729dc1db-fde2-477b-9cc8-c21276720462 · outbound

This paper cites Provably efficient algorithms for multi-objective competitive RL,.

Operator Splitting for Convex Constrained Markov Decision Processes Provably efficient algorithms for multi-objective competitive RL,

Reference 35

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raw_fallback, observed 2026-08-11T12:40:46.198587Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.641928Z digest=sha256:a4e1e9f9410cb9d49c7bd8b693b2fb03cae46c6962dc87d10ef55acdcacf1a1e

Observation 148017e3-2317-4d51-86ef-164c340ffebb · outbound

This paper cites A splitting method for optimal control,.

Operator Splitting for Convex Constrained Markov Decision Processes A splitting method for optimal control,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.187573Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.645327Z digest=sha256:9becfb00b9c02d80142c6972cac1398f204f80c43afc4c72ec1aaed6d773f1a2

Observation 335a47a6-b86e-4328-95d5-b970d8ec748d · outbound

This paper cites A unified view of entropy-regularized Markov decision processes.

Operator Splitting for Convex Constrained Markov Decision Processes A unified view of entropy-regularized Markov decision processes

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.648460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.648460Z digest=sha256:ad2198c7d37b7678479a26e1cdd488ac5c536ecbc02e06fa1f505bc5b767e06b

Observation 34500308-5375-46e9-a658-cf89b33ce04e · outbound

This paper cites A theory of regularized Markov decision processes,.

Operator Splitting for Convex Constrained Markov Decision Processes A theory of regularized Markov decision processes,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.176808Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.651895Z digest=sha256:e40e8f5998edf4bc2586022b9016925ed3537168961b5ce17fcae1163eff8177

Observation 47314e45-c403-49b2-9885-921c406adbef · outbound

This paper cites Dynamic programming through the lens of semismooth Newton-type methods,.

Operator Splitting for Convex Constrained Markov Decision Processes Dynamic programming through the lens of semismooth Newton-type methods,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.165676Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.655087Z digest=sha256:29eacc9ef7a1b69b6a1979cf166279b485f18f703961ff083e3fc92d96b9bc8d

Observation f226bed8-e293-433e-ae8c-f2f142ea9ed2 · outbound

This paper cites From optimization to control: quasi policy iteration,.

Operator Splitting for Convex Constrained Markov Decision Processes From optimization to control: quasi policy iteration,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.658357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.658357Z digest=sha256:1771e1d092b577068259a155a1298def3c459d296f66930c2ded8956a0b9e7dc

Observation c85f91e9-7369-41ab-9e12-03177f016048 · outbound

This paper cites On the minimal displacement vector of the Douglas–Rachford operator,.

Operator Splitting for Convex Constrained Markov Decision Processes On the minimal displacement vector of the Douglas–Rachford operator,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.154673Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.661823Z digest=sha256:4a7df40dfc3cea3a9cca249d232bd22d8cd831be04bba5883691ca83ddd9fad8

Observation 845b7a3d-417a-45ab-a633-b0261fba5ace · outbound

This paper cites On the Douglas–Rachford algorithm for solving possibly inconsistent optimization problems,.

Operator Splitting for Convex Constrained Markov Decision Processes On the Douglas–Rachford algorithm for solving possibly inconsistent optimization problems,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.143746Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.664885Z digest=sha256:90fd0b01c3127ec8e6196a3213b114edaaa93af0fc49bbd054d8c52a92363a24

Observation d1af1847-d264-4ecb-b59f-461b404f105a · outbound

This paper cites Infeasibility detection in alternating direction method of multipliers for convex quadratic programs,.

Operator Splitting for Convex Constrained Markov Decision Processes Infeasibility detection in alternating direction method of multipliers for convex quadratic programs,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.133546Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.668212Z digest=sha256:8ee63ab33863d09756bd7c847a623edb1c964d2d790ff860e636658636d68a57

Observation 38476989-5207-4d52-9083-c9d5b7edbc04 · outbound

This paper cites A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs.

Operator Splitting for Convex Constrained Markov Decision Processes A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:40:45.774770Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.672091Z digest=sha256:8ebec2df1d08e3926096cfc23bc879d036cea6243dd6556d0f194fa0365065ce

Observation c19741f1-0603-4eff-8ff8-a0f75088959b · outbound

This paper cites Infeasibility detection in the alternating direction method of multipliers for convex optimization,.

Operator Splitting for Convex Constrained Markov Decision Processes Infeasibility detection in the alternating direction method of multipliers for convex optimization,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.122245Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.675613Z digest=sha256:c6c5f66aad32660e55acef2db0490916e1c452656f075c6eed3d269e85898419

Observation 2d88bf23-f813-4fe2-943b-38f62e751c1b · outbound

This paper cites an unresolved cited work.

Operator Splitting for Convex Constrained Markov Decision Processes Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:40:46.108724Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.678725Z digest=sha256:7a82d6e1aa29a8ceb3570d066bef83fdaf0d6ced2b7fe0645d3eba2669422d64

Observation 1b6545ba-014c-4585-a7dd-adf545063e20 · outbound

This paper cites On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators,.

Operator Splitting for Convex Constrained Markov Decision Processes On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.096953Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.681633Z digest=sha256:2fefb90595180be57fbcd8e7e42d5830324015b10dbe449c6f6bfb5a84e41a19

Observation c69d66ec-44ed-4ae4-aa7c-882db7784a41 · outbound

This paper cites On the convergence of the coordinate descent method for convex differentiable minimization,.

Operator Splitting for Convex Constrained Markov Decision Processes On the convergence of the coordinate descent method for convex differentiable minimization,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.084852Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.684600Z digest=sha256:2c62cdf10b1e3d6b72bb43297ddb0a5318f4f6a9c5182c5426168b5818ce08e6

Observation b49bbd16-32d3-4d0c-a4da-e95a873a9931 · outbound

This paper cites Nocedal and S.

Operator Splitting for Convex Constrained Markov Decision Processes Nocedal and S

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.072601Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.687334Z digest=sha256:1adea8b5da3dfdf021d61617dec137523d288a12cb7fcbbea6425a8c02657237

Observation 9e4d7071-9aac-4c60-99b2-5ec01d98fb67 · outbound

This paper cites Operator-splitting methods for monotone affine variational inequalities, with a parallel application to optimal control,.

Operator Splitting for Convex Constrained Markov Decision Processes Operator-splitting methods for monotone affine variational inequalities, with a parallel application to optimal control,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.060999Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.690317Z digest=sha256:30aed9efe47aea811f237dcb17adcd15c363b8c40e73e735626197757a3c0c40

Observation a1b6c6ae-34c2-4999-90b9-0e8a26dfd4b6 · outbound

This paper cites Parallel alternating direction multiplier decomposition of convex programs,.

Operator Splitting for Convex Constrained Markov Decision Processes Parallel alternating direction multiplier decomposition of convex programs,

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.693417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.693417Z digest=sha256:1c6576717df712ae3bf29187b11727775d191bfdd3ae1f5b0759cfcd0790e6a1

Observation 5dbb4e01-7ed9-4674-8b68-5ef2c559d5f2 · outbound

This paper cites Natural Actor- Critic Algorithms,.

Operator Splitting for Convex Constrained Markov Decision Processes Natural Actor- Critic Algorithms,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.041883Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.696698Z digest=sha256:969bc65b5f5755893818f56c78201c07aadb7c08f4fb5cc6e5a6a2d7ac14a40c

Observation c93d3625-2ce4-4e7d-a5b2-e990d6dbc021 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Operator Splitting for Convex Constrained Markov Decision Processes Pytorch: An imperative style, high-performance deep learning library,

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.699652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.699652Z digest=sha256:8cc4b1f420fa34c43acf718f1070acaa8e640ffda2b72f6813c7ba396465caff

Observation 88f42b45-ae06-4a60-8f92-525e4980a090 · outbound

This paper cites PID accelerated value iteration algorithm,.

Operator Splitting for Convex Constrained Markov Decision Processes PID accelerated value iteration algorithm,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.022465Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.702427Z digest=sha256:da7035d32b174ffe12fc3eafb0c1a974ed3b9c1e10e875cc9e85757bd3e5517c

Observation e5599083-65e5-438d-9d0e-c179ab9b09e5 · outbound

This paper cites Scalable first-order methods for robust MDPs,.

Operator Splitting for Convex Constrained Markov Decision Processes Scalable first-order methods for robust MDPs,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:46.008711Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.705410Z digest=sha256:2fc6614f30282034a71b9b5e3e44dc794b8d0dcfce3fda74420f4ac0bab32b8c

Observation 39b06f7f-f487-4906-9d07-fdd4f6b374f1 · outbound

This paper cites Integrating a partial model into model free reinforcement learning.,.

Operator Splitting for Convex Constrained Markov Decision Processes Integrating a partial model into model free reinforcement learning.,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:45.996527Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.708307Z digest=sha256:ea566fc380e477b113e3e42fa916a93538cf2a03975e8f87b289ccbab425a16e

Observation 63fdc30f-6f3c-4af2-a99d-59108ef8521e · outbound

This paper cites Gurobi Optimizer Reference Manual,.

Operator Splitting for Convex Constrained Markov Decision Processes Gurobi Optimizer Reference Manual,

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.711404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.711404Z digest=sha256:1b4a0599a78eb8d2757444a01c4eaa299ea0cfbd9f4b8c1a95f4c7190c1b0f40

Observation 259e0a59-fbdb-4c88-a3c2-6483e6ec897c · outbound

This paper cites Safe policies for reinforcement learning via primal-dual methods,.

Operator Splitting for Convex Constrained Markov Decision Processes Safe policies for reinforcement learning via primal-dual methods,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:45.978868Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.714654Z digest=sha256:f1d58257a765638da3f31b6447a906a4f34c53a1917e364ccc569e978d621fb6

Observation 2729d892-f1e5-4e18-b5ff-3355062fa1bd · outbound

This paper cites Conic optimization via operator splitting and homogeneous self-dual embedding,.

Operator Splitting for Convex Constrained Markov Decision Processes Conic optimization via operator splitting and homogeneous self-dual embedding,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:40:45.968594Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-11T12:40:45.718057Z digest=sha256:86c7574ee28509d99efbdd115c5bd388e7c2701e8a40111b9632a9b0193503c5

Observation d61bd2c1-8f1d-44a1-b1e3-8e9084a80edd · outbound

This paper cites Reward Constrained Policy Optimization.

Operator Splitting for Convex Constrained Markov Decision Processes Reward Constrained Policy Optimization

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.721211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.721211Z digest=sha256:8e19ceb9d673c077d873b2b19efdf4859c7f8a2564b89b5fca7eb8fa5ab963ad

Observation 992f0858-c3e3-459b-ab05-cc8006d66e68 · outbound

This paper cites Markov decision processes,.

Operator Splitting for Convex Constrained Markov Decision Processes Markov decision processes,

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.724621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.724621Z digest=sha256:68f8f558aa5df11ff19c894b22fe4ab537c52ecdb805ad9c7ce1409cc0cbf311

Observation 32b6a08f-3524-4360-8b11-de9e3173d032 · outbound

This paper cites an unresolved cited work.

Operator Splitting for Convex Constrained Markov Decision Processes Unresolved cited work

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-11T12:40:45.727688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:40:45.727688Z digest=sha256:a7081df8cc6a08e43a719e337383087d142c451763602a2c04c4be19520714a0

Pith citing papers

Observation c91b5c64-12f6-42f0-b676-61bc626b43da · inbound

Joint Chance Constrained Safe-Optimal Control cites this paper.

Joint Chance Constrained Safe-Optimal Control Operator Splitting for Convex Constrained Markov Decision Processes

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-01T12:55:44.118969Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-01T01:40:08.230114Z digest=sha256:a1bc17815e117614ac12a8d1dcf9f079316412083af68bb1e85893887ac71cb8