Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:28:35.482762Z
Paper Citation Record · LEDGER
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning
As of 20 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2501.04879.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
50 of 50 outbound references displayed
- verified exact0
- verified fuzzy40
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 122e959a-67c9-4e7a-ac5d-7c0a6e5f6c8e · outbound
This paper cites an unresolved cited work.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:28:37.771644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b70a9f9b-58e7-4102-ab42-332a8231ef18 · outbound
This paper cites an unresolved cited work.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:28:37.671929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 05c0604c-6a2f-4948-9d23-e6a87ced3c65 · outbound
This paper cites Mastering the game of Go with deep neural networks and tree search,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Mastering the game of Go with deep neural networks and tree search,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.660833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3622e60e-bffa-4581-8951-a13121f04452 · outbound
This paper cites Mastering the game of Go without human knowledge,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Mastering the game of Go without human knowledge,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.650268Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 5db8c95d-6760-4ffe-abc3-c2a93abe5849 · outbound
This paper cites Language models are few-shot learners,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Language models are few-shot learners,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.497353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0a164a31-aa4a-4cf3-84f2-976c91175c1e · outbound
This paper cites an unresolved cited work.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:28:37.411769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 23d01f53-2c08-44ee-b7ba-f6e957432762 · outbound
This paper cites an unresolved cited work.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T21:28:37.400278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4b2b8e3d-3130-4d4d-bd2a-a5faa4bdb0f4 · outbound
This paper cites Policy gradient methods for reinforcement learning with function approximation,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Policy gradient methods for reinforcement learning with function approximation,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.389325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a842cc04-e702-49c5-8f40-6d12f8188980 · outbound
This paper cites Stochastic policy gradient ascent in reproducing kernel Hilbert spaces,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Stochastic policy gradient ascent in reproducing kernel Hilbert spaces,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.376239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7adc6292-3262-4fa9-a4c0-c8bba80c9715 · outbound
This paper cites Communication- efficient policy gradient methods for distributed reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Communication- efficient policy gradient methods for distributed reinforcement learning,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.185601Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0f77fce7-d027-41cf-bd2e-a7850fe97b23 · outbound
This paper cites Learning online alignments with continuous rewards policy gradient,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Learning online alignments with continuous rewards policy gradient,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:37.096965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b8cd722a-c5bf-4da5-94f8-ccfa625142e7 · outbound
This paper cites Deep reinforcement learning: A brief survey,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Deep reinforcement learning: A brief survey,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.997948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 200e934a-303b-4c48-ad61-a632750fecad · outbound
This paper cites Compressed conditional mean embeddings for model-based reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Compressed conditional mean embeddings for model-based reinforcement learning,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.929358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 3dc1d551-10ae-47ea-94b4-3ffff318b147 · outbound
This paper cites Nonparametric stochastic compositional gradient descent for Q-learning in continuous markov decision problems,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Nonparametric stochastic compositional gradient descent for Q-learning in continuous markov decision problems,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.914568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 98079f9d-a2d5-4425-99cd-5e6f00f586a4 · outbound
This paper cites DDPG-driven deep-unfolding with adaptive depth for channel estimation with sparse Bayesian learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning DDPG-driven deep-unfolding with adaptive depth for channel estimation with sparse Bayesian learning,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.900614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2b2add73-4a90-46a8-9b27-c07eabe7dd34 · outbound
This paper cites Harnessing structures for value-based planning and reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Harnessing structures for value-based planning and reinforcement learning,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.784751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 78f66b58-d38e-4016-b6a5-66dfd13b95b3 · outbound
This paper cites Tensor-based reinforcement learning for network routing,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tensor-based reinforcement learning for network routing,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.703067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 22907a49-0cc1-4a2d-8d46-9e8d9190a5e3 · outbound
This paper cites Tensor and matrix low- rank value-function approximation in reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tensor and matrix low- rank value-function approximation in reinforcement learning,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.691245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cb4db96d-1806-4bfa-b69b-b3c08c3a7fa3 · outbound
This paper cites Matrix low-rank approximation for policy gradient methods,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Matrix low-rank approximation for policy gradient methods,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.677261Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c04c2ded-70c0-4ae5-aca2-b5edce2db17e · outbound
This paper cites The approximation of one matrix by another of lower rank,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning The approximation of one matrix by another of lower rank,
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:34.407234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f5299b5-1498-4d4f-a376-a91e83d091c6 · outbound
This paper cites Markovsky, Low rank approximation.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Markovsky, Low rank approximation
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.561531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 7c0854f6-8acd-435b-bdc3-1995b71acd88 · outbound
This paper cites Generalized low rank models,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Generalized low rank models,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.493981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 56c3f893-6226-4ffb-ab6d-49655587652c · outbound
This paper cites Tensor decompositions and applications,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tensor decompositions and applications,
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:34.679224Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2149ad7d-f4f9-4f55-bdf0-82756af82d65 · outbound
This paper cites Tensor decomposition for signal processing and machine learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tensor decomposition for signal processing and machine learning,
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:34.683438Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 608694a9-9143-4a03-84ca-5919484b4577 · outbound
This paper cites Flambe: Structural complexity and representation learning of low rank MDPs,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Flambe: Structural complexity and representation learning of low rank MDPs,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.469310Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9a09bca2-8188-4e97-b859-37b0a4881f4e · outbound
This paper cites Representation learning for online and offline RL in low-rank MDPs,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Representation learning for online and offline RL in low-rank MDPs,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.418257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c89cb07b-49be-4c49-ac3f-b5cb756fb4d0 · outbound
This paper cites Incremental stochastic factorization for online reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Incremental stochastic factorization for online reinforcement learning,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.292215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 68b63fe3-0ee1-440a-81cd-93381dd999cc · outbound
This paper cites Contextual decision processes with low Bellman rank are pac-learnable,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Contextual decision processes with low Bellman rank are pac-learnable,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.280976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d4d17fd4-8b0a-4c1b-b0b5-e57d58ed2ca1 · outbound
This paper cites Reinforcement learning of POMDPs using spectral methods,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Reinforcement learning of POMDPs using spectral methods,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.217582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 27f9b7a6-ad12-4fd4-a3af-4ded07fa8b27 · outbound
This paper cites Tesseract: Tensorised actors for multi-agent reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tesseract: Tensorised actors for multi-agent reinforcement learning,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.088814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 490518e0-6a2d-4957-8880-2df69eb030a0 · outbound
This paper cites Overcoming the long horizon barrier for sample-efficient reinforcement learning with latent low-rank structure,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Overcoming the long horizon barrier for sample-efficient reinforcement learning with latent low-rank structure,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.076773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1e36f660-d43b-4b34-badb-91a4e1d792c6 · outbound
This paper cites Sample efficient reinforcement learning via low-rank matrix estimation,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Sample efficient reinforcement learning via low-rank matrix estimation,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.065430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 4bf59ec7-3f79-4510-9170-653b195741b7 · outbound
This paper cites Low-rank state-action value-function approximation,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Low-rank state-action value-function approximation,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.054337Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 86881583-83a3-4073-882e-8f72c412f6d9 · outbound
This paper cites Matrix low-rank trust region policy optimization,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Matrix low-rank trust region policy optimization,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:36.042001Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b2396db4-87fa-4186-ba5f-8a6e278029e3 · outbound
This paper cites Optimization for reinforcement learning: From a single agent to cooperative agents,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Optimization for reinforcement learning: From a single agent to cooperative agents,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.957147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 29ef7b77-1d80-49f1-8db5-1c2e1ee9dc29 · outbound
This paper cites Simple statistical gradient-following algorithms for connectionist reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Simple statistical gradient-following algorithms for connectionist reinforcement learning,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.909507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 9ad216e9-59ac-4f96-8fcc-315e5e9a5fa5 · outbound
This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning High-Dimensional Continuous Control Using Generalized Advantage Estimation
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:35.211211Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a04e524-a29f-4a20-8504-23a78c33b608 · outbound
This paper cites Variance reduction tech- niques for gradient estimates in reinforcement learning.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Variance reduction tech- niques for gradient estimates in reinforcement learning
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.898632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 623ed208-64b1-4fbf-82c8-7a56f22ca0ec · outbound
This paper cites Actor-critic algorithms,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Actor-critic algorithms,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.888075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 8166db67-a7a4-437b-871f-df0ebdf0aca5 · outbound
This paper cites A natural policy gradient,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning A natural policy gradient,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.878000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation a3a55557-6df2-4b3c-9f7e-b35541ace1a5 · outbound
This paper cites Approximately optimal approximate rein- forcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Approximately optimal approximate rein- forcement learning,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.867295Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2d2f2fba-7cb7-4dab-aa02-8eba9a53b1d7 · outbound
This paper cites Trust region policy optimization,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Trust region policy optimization,
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.819459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2167e4c2-f01f-496c-b46a-e87e41360cde · outbound
This paper cites Proximal Policy Optimization Algorithms.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Proximal Policy Optimization Algorithms
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:35.333560Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42bb3872-9e47-4a15-ab3e-509f09d3f7be · outbound
This paper cites PARAFAC. tutorial and applications,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning PARAFAC. tutorial and applications,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.669101Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 45eb0b67-e29c-4df7-a879-9e968b44c4df · outbound
This paper cites Tensor low-rank approximation of finite- horizon value functions,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Tensor low-rank approximation of finite- horizon value functions,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.656184Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 05279c83-5597-444d-b61c-66b07434596b · outbound
This paper cites Amari, Differential-geometrical methods in statistics.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Amari, Differential-geometrical methods in statistics
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.644411Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 2eb51ce7-8bce-44c1-acc4-3a5f40b91082 · outbound
This paper cites Stochastic model-based minimization of weakly convex functions,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Stochastic model-based minimization of weakly convex functions,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.633266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation ba77206a-c882-4fc6-bd80-853c10ab913c · outbound
This paper cites Online code repository: Tensor low-rank approximation for policy-gradient methods in reinforcement learning,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Online code repository: Tensor low-rank approximation for policy-gradient methods in reinforcement learning,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.621962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 16c87049-d1b2-4d70-89da-b5fdbe060899 · outbound
This paper cites OpenAI Gym.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning OpenAI Gym
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:28:35.477676Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7bfbd494-a15e-409c-bbf2-2a86056271cd · outbound
This paper cites Radial basis functions,.
Multilinear Tensor Low-Rank Approximation for Policy-Gradient Methods in Reinforcement Learning Radial basis functions,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T21:28:35.574825Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.