Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:37:15.446600Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 1 inbound Pith citation observation for arXiv:2501.04565.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: paper_references, paper_reference_links, observed 2026-08-10T21:37:15.446600Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T16:17:12.059466Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T16:17:12.487306Z
74 of 74 outbound references displayed
External citation measurements
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Observation e6e2a191-98de-446b-8b1b-1cfa9c2015cb · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Robust principal component analysis?
Reference 1
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Matrix and tensor completion algorithms for background model initialization: A comparative evaluation,
Reference 2
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Observation 84377e05-c4a1-4443-b1f0-70fe34698673 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA A novel anomaly detection scheme based on principal component classifier,
Reference 3
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Observation b1410d83-559b-4353-8e8a-4a08813f243a · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA On the applications of robust PCA in image and video processing,
Reference 4
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Observation 34313a3e-6dcc-486f-bb7a-972a3683c8ed · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor decompositions and applications,
Reference 5
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Observation 7bb2757a-28fd-492c-8506-ea4baf9e3b6f · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor decomposition for signal processing and machine learning,
Reference 6
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Reference 7
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor robust principal component analysis: Exact recovery of corrupted low-rank tensors via convex optimization,
Reference 8
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Novel methods for multilinear data completion and de-noising based on tensor-svd,
Reference 9
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor robust principal component analysis with a new tensor nuclear norm,
Reference 10
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Observation c7d871d6-564e-4362-9e3c-3a2521d4b2dd · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Foundations of the parafac procedure: Models and conditions for an “explanatory
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor rank and the ill-posedness of the best low-rank approximation problem,
Reference 12
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Observation b8269129-c788-4572-a541-d80c53fb3ba2 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Some mathematical notes on three-mode factor analysis,
Reference 13
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Observation de1fcfa9-b42e-4913-8a3d-87c76643ab83 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Square deal: Lower bounds and improved relaxations for tensor recovery,
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Observation 88b7d204-f7ba-4431-bb81-24a0527a9a36 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tree adaptive approximation in the hier- archical tensor format,
Reference 15
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Observation 3983f0d4-5686-4035-a341-76292f4bb6cd · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor-train decomposition,
Reference 16
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Observation a35d61d2-3022-433f-8df1-b76af8b342d4 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor Ring Decomposition
Reference 17
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Facial recog- nition using tensor-tensor decompositions,
Reference 18
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Outlier-robust tensor PCA,
Reference 19
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Observation ab7f1ea1-0acf-4d81-9ca7-dcec43c8663f · outbound
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Reference 21
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Observation bfef01b0-11bd-4c4e-8b96-cfec5c7dc7d5 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Fourth-order Tensors with Multidimensional Discrete Transforms
Reference 22
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA A Fast Algorithm for Cosine Transform Based Tensor Singular Value Decomposition
Reference 23
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Robust tensor completion using transformed tensor singular value decomposition,
Reference 24
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Dictionary learning with low-rank coding coefficients for tensor completion,
Reference 25
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA The twist tensor nuclear norm for video completion,
Reference 26
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Observation 5c584e13-1329-42da-a4f5-e883076eb72e · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Improved robust tensor principal com- ponent analysis via low-rank core matrix,
Reference 27
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Mixed noise removal in hyperspectral image via low-fibered-rank regularization,
Reference 28
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Observation 6116ff3d-154b-49f3-9229-5cc8048775c0 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm,
Reference 29
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Reference 30
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Observation 0985df8f-b4dd-4eac-b3a1-32ebf10c8707 · outbound
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Reference 32
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Low-rank tensor com- pletion based on self-adaptive learnable transforms,
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Reference 36
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Multiplex trans- formed tensor decomposition for multidimensional image recovery,
Reference 37
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Reference 38
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Reference 39
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent
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Reference 42
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Observation 85e3379a-1f19-4303-919a-035afef86bfb · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Accelerating ill-conditioned low-rank matrix estimation via scaled gradient descent,
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Fast and provable tensor robust principal component analysis via scaled gradient descent,
Reference 44
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Observation 61c38c3f-1a56-46d8-91db-3816052696b9 · outbound
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Reference 45
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Deep unfolded tensor robust PCA with self-supervised learning,
Reference 46
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Reference 47
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Factorization strategies for third-order tensors,
Reference 48
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Robust block tensor principal component analysis,
Reference 49
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Observation 111e40c8-87c1-4763-99b7-3556b19004ca · outbound
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Reference 50
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Reference 51
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Deep unfolded robust PCA with application to clutter suppression in ultrasound,
Reference 52
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA A deep-unfolded reference-based RPCA network for video foreground- background separation,
Reference 53
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Interpretable neural networks for video separation: Deep unfolding RPCA with foreground masking,
Reference 54
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA RPCANet: Deep unfolding RPCA based infrared small target detection,
Reference 55
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Denise: Deep learning based robust PCA for positive semidefinite matrices,
Reference 56
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Reference 57
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Scene background initialization: A taxonomy,
Reference 58
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Extensive benchmark and survey of modeling methods for scene background initialization,
Reference 59
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
Reference 60
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA He was the recipient of the IEEE Signal Processing Society Young Author Best Paper Award in
Reference 63
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Observation 3b7e8612-19f9-4eaf-b20a-756178ad9f11 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA The first term tr(∆L ∗ Σ⋆ ∗ ∆⊤ L ) is closely related to dist(Lk, Rk; L⋆, R⋆), so we will focus on relating M1 and M2 to dist(Lk, Rk; L⋆, R⋆)
Reference 65
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Observation 183e7b64-08a2-492f-b3d8-f7641d1594b3 · outbound
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Reference 66
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Observation 29bd3ee5-216d-47a8-b111-8084c25c7516 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA IEEE JOURNAL, VOL
Reference 67
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Observation 60f9c3a2-f92e-486b-9bfd-19b7818a2d4c · outbound
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Reference 68
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Lemma 13
Reference 69
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Reference 70
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Observation 7a9f0382-f4eb-472f-bc2d-8be1739e12b3 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Together, we have T2 ≤ η∥L⋆ ∗ Σ −1/2 ⋆ ∥2,∞∥∆R ∗ Σ 1/2 ⋆ ∥2∥R♮ ∗ (R⊤ ♮ ∗ R♮)−1 ∗ Σ 1/2 ⋆ ∥2 ≤ η ε 1 − ε r µR I1 τ kσmin(X⋆)
Reference 71
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Thus, by Lemma 5, Lemma 3 and 11, we get T3 ≤ η∥∆S ∥2,∞∥R♮ ∗ (R⊤ ♮ ∗ R♮)−1 ∗ Σ 1/2 ⋆ ∥2 ≤ η √αI2I3 1 − ε ∥∆S ∥∞ ≤ 2η √αI2I3 1 − ε ζk+1 ≤ 6η √αI3 1 − ε 1√I1 µRτ kσmin(X⋆)
Reference 72
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Observation b9a934b8-76f9-48c6-abeb-049ac9935ae9 · outbound
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Reference 73
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Observation 36397379-fd71-48e1-afda-865b96ca3015 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA The proof is concluded by substituting τ = 1 − 0.6η
Reference 74
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Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
Reference 2016
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Observation 0308512d-679b-4639-bd22-f6cc4be68271 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA IEEE JOURNAL, VOL
Reference 2019
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Observation 983d89e2-ff0f-49ce-aebe-54bfde5fe106 · outbound
Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA Tensor Computation for Data Analysis
Reference 2023
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Observation d7474fa1-273c-4474-b21f-c71d0d66f4c2 · inbound
Beyond Motion Cues and Structural Sparsity: Revisiting Small Moving Target Detection Learnable Scaled Gradient Descent for Guaranteed Robust Tensor PCA
Reference 31
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