Paper Citation Record · LEDGER

A Scalable Factorization Approach for High-Order Structured Tensor Recovery

As of 18 August 2026, this Paper Citation Record lists 92 of 92 outbound references and 5 inbound Pith citation observations for arXiv:2506.16032.

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

pith.paper-citation-record.v1
2506.16032 v1

Coverage vector

measured 92 of 92 reference resolution

Typed states for the displayed outbound observations.

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measured 97 of 97 standing notices

One-hop event checks from named stored sources.

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measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:06:49.209508Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:30.430769Z

Reference resolution

92 of 92 outbound references displayed

verified exact6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3eaea52f-eb6a-4706-b395-9d180cfc4e81 · outbound

This paper cites Interior-point method for nuclear norm approximation with application to system identification.SIAM Journal on Matrix Analysis and Applications, 31(3):1235–1256, 2010.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Interior-point method for nuclear norm approximation with application to system identification.SIAM Journal on Matrix Analysis and Applications, 31(3):1235–1256, 2010

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.591289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b672003a-be26-4932-8bd7-dbeefcc55d3f · outbound

This paper cites Designing tensor-train deep neural networks for time-varying mimo channel estimation.IEEE Journal of Selected Topics in Signal Processing, 15(3):759–773, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Designing tensor-train deep neural networks for time-varying mimo channel estimation.IEEE Journal of Selected Topics in Signal Processing, 15(3):759–773, 2021

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.677952Z

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Observation 04ec4fb3-5c67-46d8-a70b-77cc65dc8ea7 · outbound

This paper cites Fast and robust quantum state tomography from few basis measurements.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Fast and robust quantum state tomography from few basis measurements

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.759414Z

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Observation b5021df2-9cfa-45b0-8041-3f793d6fe1eb · outbound

This paper cites Quantum state tomography with tensor train cross approximation.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Quantum state tomography with tensor train cross approximation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.823747Z

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Observation 9f967d32-0a32-4f31-901d-bf4e9be3bcd9 · outbound

This paper cites Quantum state tomography for matrix product density operators.IEEE Transactions on Information Theory, 70(7):5030–5056, 2024.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Quantum state tomography for matrix product density operators.IEEE Transactions on Information Theory, 70(7):5030–5056, 2024

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.885205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e414fbb-3eb7-42ec-a4bd-f774b3058e5d · outbound

This paper cites Mixture-rank matrix approximation for collaborative filtering.Advances in Neural Information Processing Systems, 30, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Mixture-rank matrix approximation for collaborative filtering.Advances in Neural Information Processing Systems, 30, 2017

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:09.952525Z

Source-reported events for the cited work

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Observation 56ae6002-3485-4b58-8e52-05c1e5230cd7 · outbound

This paper cites Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach.Electronic Journal of Statistics, 14(1):413–457, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach.Electronic Journal of Statistics, 14(1):413–457, 2020

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.017654Z

Source-reported events for the cited work

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Observation 02388854-4c95-49ff-867c-f578a7c5c0d4 · outbound

This paper cites Analysis of a complex of statistical variables into principal components.Journal of educational psychology, 24(6):417, 1933.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Analysis of a complex of statistical variables into principal components.Journal of educational psychology, 24(6):417, 1933

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.098307Z

Source-reported events for the cited work

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Observation 4e8b73e4-7328-4ce0-a089-51cb4c2570b9 · outbound

This paper cites Microbial co-occurrence relationships in the human microbiome.PLoS computational biology, 8(7):e1002606, 2012.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Microbial co-occurrence relationships in the human microbiome.PLoS computational biology, 8(7):e1002606, 2012

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.160954Z

Source-reported events for the cited work

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Observation 0fe6bd4c-470d-467a-952b-dcac00dabbc2 · outbound

This paper cites Latent space models for dynamic networks.Journal of the American Statistical Association, 110(512):1646–1657, 2015.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Latent space models for dynamic networks.Journal of the American Statistical Association, 110(512):1646–1657, 2015

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.241853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34f6dc97-e98f-46d3-99f4-64700fc8c6ca · outbound

This paper cites Poisson noise reduction with non-local pca.Journal of mathematical imaging and vision, 48(2):279–294, 2014.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Poisson noise reduction with non-local pca.Journal of mathematical imaging and vision, 48(2):279–294, 2014

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.317621Z

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Observation ea5732e2-a6fc-4895-b46f-d0a6148a24bd · outbound

This paper cites Expressive power of recurrent neural networks.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Expressive power of recurrent neural networks

Reference 12

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Source-reported events for the cited work

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Observation c882aab8-8551-4b36-a3eb-a4299f0e6647 · outbound

This paper cites Supervised learning with tensor networks.Advances in neural infor- mation processing systems, 29, 2016.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Supervised learning with tensor networks.Advances in neural infor- mation processing systems, 29, 2016

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.438799Z

Source-reported events for the cited work

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Observation 9a4b4d5f-8f24-430d-81e2-af61031f17f2 · outbound

This paper cites Tensor-train recurrent neural networks for video classifica- tion.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor-train recurrent neural networks for video classifica- tion

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:10.555896Z

Source-reported events for the cited work

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Observation a6886033-13bd-42e3-a9bc-2f50c7e55e74 · outbound

This paper cites Tensorizing neural networks.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensorizing neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.901021Z

Source-reported events for the cited work

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Observation 9b47a724-32f2-4608-bc61-5a518ee7ce45 · outbound

This paper cites Compressing recurrent neural network with tensor train.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Compressing recurrent neural network with tensor train

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.892707Z

Source-reported events for the cited work

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Observation 2e07f643-4177-487c-b9c2-99b2b1164ad9 · outbound

This paper cites Long-term forecasting using tensor-train rnns.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Long-term forecasting using tensor-train rnns

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.882989Z

Source-reported events for the cited work

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Observation 74452945-232e-4728-b3a3-b44b3252b2ae · outbound

This paper cites A tensorized transformer for language modeling.Advances in neural information processing systems, 32, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery A tensorized transformer for language modeling.Advances in neural information processing systems, 32, 2019

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.013788Z

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Observation fecf8875-3c5c-48d0-bcb1-1c5150b6739a · outbound

This paper cites Tensor methods and recommender systems.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(3):e1201, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor methods and recommender systems.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(3):e1201, 2017

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.867748Z

Source-reported events for the cited work

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Observation b42ccbdf-f194-4b2c-8de9-4c236ec98a38 · outbound

This paper cites Some mathematical notes on three-mode factor analysis.Psychometrika, 31(3):279–311, 1966.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Some mathematical notes on three-mode factor analysis.Psychometrika, 31(3):279–311, 1966

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.858215Z

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Observation ff557c35-0b09-44f1-b475-63012263918d · outbound

This paper cites Oseledets.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Oseledets

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.233608Z

Source-reported events for the cited work

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Observation 20b3f79d-688e-42ee-8234-bdf3832b4785 · outbound

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A Scalable Factorization Approach for High-Order Structured Tensor Recovery Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:53:12.844511Z

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Observation 060a313e-a8f5-4f2c-8efa-6ebdd899af23 · outbound

This paper cites On the uniqueness of multilinear decomposition of n-way arrays.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery On the uniqueness of multilinear decomposition of n-way arrays

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.835603Z

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Observation 5d51c019-ad6f-4bf3-9898-32032c9c1170 · outbound

This paper cites Parsimonious tensor response regression.Journal of the American Statistical Associa- tion, 112(519):1131–1146, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Parsimonious tensor response regression.Journal of the American Statistical Associa- tion, 112(519):1131–1146, 2017

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.827386Z

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Observation ed949090-cafb-434c-9349-4040669cfad4 · outbound

This paper cites Tucker tensor regression and neuroimaging analysis.Statistics in Biosciences, 10:520–545, 2018.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tucker tensor regression and neuroimaging analysis.Statistics in Biosciences, 10:520–545, 2018

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.819104Z

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Observation 878897a7-dfb4-45bb-a5b7-0812ee73cd66 · outbound

This paper cites Hyperspectral image, video compression using sparse tucker tensor decomposition.IET Image Processing, 15(4):964–973, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Hyperspectral image, video compression using sparse tucker tensor decomposition.IET Image Processing, 15(4):964–973, 2021

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.810036Z

Source-reported events for the cited work

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Observation 0d9c543d-5e00-416d-8f8b-bed1666d6d38 · outbound

This paper cites Multilinear tensor regression for longitudinal relational data.The annals of applied statistics, 9(3):1169, 2015.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Multilinear tensor regression for longitudinal relational data.The annals of applied statistics, 9(3):1169, 2015

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.801481Z

Source-reported events for the cited work

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Observation 592f3ce5-376f-4b6c-a63d-970470030e7d · outbound

This paper cites Efficient quantum state tomography.Nature communications, 1(1):149, 2010.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Efficient quantum state tomography.Nature communications, 1(1):149, 2010

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.251167Z

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Observation 2026b290-00cc-4a3a-b2ec-be37eb232b41 · outbound

This paper cites Efficient tomography of a quantum many-body system.Nature Physics, 13(12):1158–1162, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Efficient tomography of a quantum many-body system.Nature Physics, 13(12):1158–1162, 2017

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.787201Z

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Observation fbddecb7-116d-4fd9-86c9-695d546e7e5a · outbound

This paper cites Scalable quantum tomography with fidelity estimation.Physical Review A, 101(3):032321, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Scalable quantum tomography with fidelity estimation.Physical Review A, 101(3):032321, 2020

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.776082Z

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Observation bae33c25-1f41-48f6-96a7-d1f004114a91 · outbound

This paper cites Matrix product density operators: Simulation of finite-temperature and dissipative systems.Physical review letters, 93(20):207204, 2004.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Matrix product density operators: Simulation of finite-temperature and dissipative systems.Physical review letters, 93(20):207204, 2004

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.258510Z

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Observation 08f40f50-1c2c-4703-a643-d15ea8fdd244 · outbound

This paper cites Matrix product operator representations.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Matrix product operator representations

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.261066Z

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Observation b3242e6c-3ef4-456c-b3c9-83e57f7ab090 · outbound

This paper cites Positive tensor network approach for simulating open quantum many-body systems.Physical review letters, 116(23):237201, 2016.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Positive tensor network approach for simulating open quantum many-body systems.Physical review letters, 116(23):237201, 2016

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.756901Z

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Observation e56ec4b2-5050-43e7-9b81-fe4c823b463c · outbound

This paper cites Efficient description of many-body systems with matrix product density operators.PRX Quantum, 1(1):010304, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Efficient description of many-body systems with matrix product density operators.PRX Quantum, 1(1):010304, 2020

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.748237Z

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Observation 4c04fa16-05e5-4e1f-80da-c82c15cb5c58 · outbound

This paper cites On manifolds of tensors of fixed tt-rank.Nu- merische Mathematik, 120(4):701–731, 2012.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery On manifolds of tensors of fixed tt-rank.Nu- merische Mathematik, 120(4):701–731, 2012

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.739735Z

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Observation cc951cd1-59ca-46f0-8ae8-c48e7ad13af9 · outbound

This paper cites A singular value thresholding algorithm for matrix completion.SIAM Journal on optimization, 20(4):1956–1982, 2010.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery A singular value thresholding algorithm for matrix completion.SIAM Journal on optimization, 20(4):1956–1982, 2010

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.731478Z

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Observation d6be22e1-429d-46f3-862a-5e036bd8a487 · outbound

This paper cites Tensor decompositions for signal processing applications: From two-way to multiway component analysis.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor decompositions for signal processing applications: From two-way to multiway component analysis

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.723010Z

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Observation 34dafc33-75d6-422f-b7b8-594d08bf26a9 · outbound

This paper cites Canonical polyadic de- composition with a columnwise orthonormal factor matrix.SIAM Journal on Matrix Analysis and Applications, 33(4):1190–1213, 2012.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Canonical polyadic de- composition with a columnwise orthonormal factor matrix.SIAM Journal on Matrix Analysis and Applications, 33(4):1190–1213, 2012

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.713895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 46110e0b-6e4d-441f-ac68-3f94af8f3b3a · outbound

This paper cites Probabilistic tensor canonical polyadic decomposition with orthogonal factors.IEEE Transactions on Signal Processing, 65(3):663–676, 2016.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Probabilistic tensor canonical polyadic decomposition with orthogonal factors.IEEE Transactions on Signal Processing, 65(3):663–676, 2016

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.704546Z

Source-reported events for the cited work

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Observation 3760b808-239f-4f9c-a581-ab1ad4d0a31a · outbound

This paper cites Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.279977Z

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Observation cba053ce-2f04-4823-b1b8-8db2651cca21 · outbound

This paper cites Nonconvex low-rank tensor completion from noisy data.Advances in neural information processing systems, 32, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Nonconvex low-rank tensor completion from noisy data.Advances in neural information processing systems, 32, 2019

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.695042Z

Source-reported events for the cited work

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Observation feec14c8-ccb1-4456-bedc-3ee7cc8640d7 · outbound

This paper cites Sparse tensor additive regression.Journal of machine learning research, 22(64):1–43, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Sparse tensor additive regression.Journal of machine learning research, 22(64):1–43, 2021

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.685297Z

Source-reported events for the cited work

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Observation 7a5ad92a-5354-46c9-988b-cb0c133d415a · outbound

This paper cites An optimal statistical and computational framework for generalized tensor estimation.The Annals of Statistics, 50(1):1–29, 2022.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery An optimal statistical and computational framework for generalized tensor estimation.The Annals of Statistics, 50(1):1–29, 2022

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.674080Z

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Observation 0e48fa6c-bdc3-4908-96a3-8e7e78d10aaa · outbound

This paper cites On polynomial time methods for exact low-rank tensor completion.Foundations of Computational Mathematics, 19(6):1265–1313, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery On polynomial time methods for exact low-rank tensor completion.Foundations of Computational Mathematics, 19(6):1265–1313, 2019

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.664514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1baaa813-b990-4f49-9156-646002c78453 · outbound

This paper cites Scaling and scalability: Provable nonconvex low-rank tensor estimation from incomplete measurements.Journal of Machine Learning Research, 23(163):1–77, 2022.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Scaling and scalability: Provable nonconvex low-rank tensor estimation from incomplete measurements.Journal of Machine Learning Research, 23(163):1–77, 2022

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.653914Z

Source-reported events for the cited work

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Observation d0700b47-fff1-4ba9-ab04-73005ab5e2c2 · outbound

This paper cites Guaranteed nonconvex factorization approach for tensor train recovery.Journal of Machine Learning Research, 25(383):1–48, 2024.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Guaranteed nonconvex factorization approach for tensor train recovery.Journal of Machine Learning Research, 25(383):1–48, 2024

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.643986Z

Source-reported events for the cited work

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Observation f8f40ccb-0901-4bed-b39a-cef6e4a32c54 · outbound

This paper cites Provable tensor-train format tensor completion by riemannian opti- mization.Journal of Machine Learning Research, 23(123):1–77, 2022.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Provable tensor-train format tensor completion by riemannian opti- mization.Journal of Machine Learning Research, 23(123):1–77, 2022

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.634578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4b634630-94fd-4420-ac75-df19419e4792 · outbound

This paper cites Deep transfer tensor decomposition with orthogonal constraint for recommender systems.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Deep transfer tensor decomposition with orthogonal constraint for recommender systems

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.624479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1769a45d-2c6f-4401-902c-71f1da717e22 · outbound

This paper cites Tensor decompositions for learning latent variable models.Journal of machine learning research, 15:2773–2832, 2014.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor decompositions for learning latent variable models.Journal of machine learning research, 15:2773–2832, 2014

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.613394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0af261c5-c8cd-4e45-a41e-10e323c1ef83 · outbound

This paper cites Low-rank matrix completion using alternating mini- mization.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Low-rank matrix completion using alternating mini- mization

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.603451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2f4bff27-2243-4fdc-81c4-6e7354d48c19 · outbound

This paper cites Low-rank solutions of linear matrix equations via procrustes flow.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Low-rank solutions of linear matrix equations via procrustes flow

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.592636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dcb4f174-05c0-4a9e-8aa4-54e5f27c0ba1 · outbound

This paper cites A unified computational and statistical framework for noncon- vex low-rank matrix estimation.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery A unified computational and statistical framework for noncon- vex low-rank matrix estimation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.582600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c9b324d6-905a-44e5-8b63-c27b5f0abb4d · outbound

This paper cites Global optimality in low-rank matrix optimiza- tion.IEEE Transactions on Signal Processing, 66(13):3614–3628, 2018.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Global optimality in low-rank matrix optimiza- tion.IEEE Transactions on Signal Processing, 66(13):3614–3628, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.572176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e5a06c9c-49a5-400e-b9e1-be444afa0291 · outbound

This paper cites Nonconvex robust low-rank matrix recovery.SIAM Journal on Optimization, 30(1):660–686, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Nonconvex robust low-rank matrix recovery.SIAM Journal on Optimization, 30(1):660–686, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.316585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88e1b1d9-41b5-490d-825a-859cfe0e835e · outbound

This paper cites Accelerating ill-conditioned low-rank matrix estimation via scaled gradient descent.J.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Accelerating ill-conditioned low-rank matrix estimation via scaled gradient descent.J

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.556824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6fa730d1-7e0f-4fc6-bd0a-7a76c0ea8361 · outbound

This paper cites Beyond procrustes: Balancing-free gradient descent for asymmetric low-rank matrix sensing.IEEE Transactions on Signal Processing, 69:867–877, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Beyond procrustes: Balancing-free gradient descent for asymmetric low-rank matrix sensing.IEEE Transactions on Signal Processing, 69:867–877, 2021

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.546905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 28ab9f1c-428d-43bc-a53b-75bc6d4b0232 · outbound

This paper cites Fast and provable tensor robust principal component analysis via scaled gradient descent.Information and Inference: A Journal of the IMA, 12(3):iaad019, 2023.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Fast and provable tensor robust principal component analysis via scaled gradient descent.Information and Inference: A Journal of the IMA, 12(3):iaad019, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.537082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf0ecd49-aad7-4bf6-879f-3ed54a1c978d · outbound

This paper cites Tensor Completion by Alternating Minimization under the Tensor Train (TT) Model.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor Completion by Alternating Minimization under the Tensor Train (TT) Model

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:53:12.237597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f223a97b-05fd-432a-a83e-2734d6cd6809 · outbound

This paper cites High-order tensor completion via gradient-based optimization under tensor train format.Signal Processing: Image Communication, 73:53–61, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery High-order tensor completion via gradient-based optimization under tensor train format.Signal Processing: Image Communication, 73:53–61, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.527229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d9ae107b-245c-4980-8d55-65d3d5a0d3ba · outbound

This paper cites Low rank tensor recovery via iterative hard threshold- ing.Linear Algebra and its Applications, 523:220–262, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Low rank tensor recovery via iterative hard threshold- ing.Linear Algebra and its Applications, 523:220–262, 2017

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.516145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 407996a1-17a4-4fb9-a284-ca50bd6cc45b · outbound

This paper cites Tensor completion in hierarchical tensor representa- tions.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor completion in hierarchical tensor representa- tions

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.505740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a9bbf89e-500c-4d1c-8344-cfa6158ced01 · outbound

This paper cites Non-convex projected gradient descent for generalized low-rank tensor regression.The Journal of Machine Learning Research, 20(1):172–208, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Non-convex projected gradient descent for generalized low-rank tensor regression.The Journal of Machine Learning Research, 20(1):172–208, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.497003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bd9a6641-6697-466c-ab38-1efe0e969319 · outbound

This paper cites Low-rank tensor completion by riemannian optimization.BIT Numerical Mathematics, 54(2):447–468, 2014.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Low-rank tensor completion by riemannian optimization.BIT Numerical Mathematics, 54(2):447–468, 2014

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.487360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 25868d3e-3469-4223-a57a-afaeaf976291 · outbound

This paper cites Tensor train completion: local recovery guarantees via Riemannian optimization.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor train completion: local recovery guarantees via Riemannian optimization

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:53:12.225259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f3054bed-ec07-4615-96b8-8c09b75c2008 · outbound

This paper cites Tensor completion using low-rank tensor train decomposition by riemannian optimization.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor completion using low-rank tensor train decomposition by riemannian optimization

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.478046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 33615cd8-0441-4ab3-83a8-fe6a757e6648 · outbound

This paper cites Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:53:12.213535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6628e924-082a-4ea3-bcb8-4f216c30d83d · outbound

This paper cites Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:53:12.201153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cf15d043-1fa7-4518-a6ea-ac2d97d5e8ec · outbound

This paper cites Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition

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Resolution: verified exact; local_arxiv, observed 2026-08-06T23:53:12.188292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7a8be15a-4136-4164-9222-3e66d723c970 · outbound

This paper cites Princeton University Press, 2008.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Princeton University Press, 2008

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:11.995793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9602302-aa5b-42b3-b281-82bd7fc71e79 · outbound

This paper cites Cambridge University Press, 2017.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Cambridge University Press, 2017

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:12.463676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 642319ee-9e53-4049-a144-6393e1097edc · outbound

This paper cites Solving random quadratic systems of equations is nearly as easy as solving linear systems.Advances in Neural Information Processing Systems, 28, 2015.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Solving random quadratic systems of equations is nearly as easy as solving linear systems.Advances in Neural Information Processing Systems, 28, 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0e9b166e-bd36-411e-828c-2b8af6117fa0 · outbound

This paper cites Phase retrieval via wirtinger flow: Theory and algorithms.IEEE Transactions on Information Theory, 61(4):1985–2007, 2015.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Phase retrieval via wirtinger flow: Theory and algorithms.IEEE Transactions on Information Theory, 61(4):1985–2007, 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a098fa14-cb35-4710-be9f-6d61896c4e0d · outbound

This paper cites an unresolved cited work.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-06T23:53:12.436969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 42a94f56-063a-4617-b582-103cf1b007e1 · outbound

This paper cites Nonconvex optimization meets low-rank matrix factorization: An overview.IEEE Transactions on Signal Processing, 67(20):5239–5269, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Nonconvex optimization meets low-rank matrix factorization: An overview.IEEE Transactions on Signal Processing, 67(20):5239–5269, 2019

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Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:12.113695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94029b38-4ce4-4644-abd5-84f8c833341f · outbound

This paper cites A deterministic theory for exact non-convex phase retrieval.IEEE Transac- tions on Signal Processing, 68:4612–4626, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery A deterministic theory for exact non-convex phase retrieval.IEEE Transac- tions on Signal Processing, 68:4612–4626, 2020

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a6ccdac2-8eda-4de7-bdb3-b7fa6cba142b · outbound

This paper cites Hierarchical singular value decomposition of tensors.SIAM journal on matrix analysis and applications, 31(4):2029–2054, 2010.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Hierarchical singular value decomposition of tensors.SIAM journal on matrix analysis and applications, 31(4):2029–2054, 2010

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ab09970d-1ecf-427e-8c37-1a3ca165f0fa · outbound

This paper cites Optimization on the hierarchical tucker manifold–applications to tensor completion.Linear Algebra and its Applications, 481:131–173, 2015.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Optimization on the hierarchical tucker manifold–applications to tensor completion.Linear Algebra and its Applications, 481:131–173, 2015

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 18154b20-2522-4e2f-8a7f-08380bc6f89a · outbound

This paper cites Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2e01ee3e-222a-4b20-9992-c58986bf76df · outbound

This paper cites Tensor networks for complex quantum systems.Nature Reviews Physics, 1(9):538–550, 2019.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor networks for complex quantum systems.Nature Reviews Physics, 1(9):538–550, 2019

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 71458a96-08cc-4763-a572-ab15a0da6b02 · outbound

This paper cites Tensor learning for regression.IEEE Transactions on Image Processing, 21(2):816–827, 2011.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor learning for regression.IEEE Transactions on Image Processing, 21(2):816–827, 2011

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0177318c-82f4-4799-8b10-41b9a73493cf · outbound

This paper cites Sparse and low-rank tensor estimation via cubic sketchings.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Sparse and low-rank tensor estimation via cubic sketchings

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ea4d9396-ef8a-474a-a5c1-46a2dbeadde5 · outbound

This paper cites Tensor regression with applications in neuroimaging data analysis.Journal of the American Statistical Association, 108(502):540–552, 2013.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Tensor regression with applications in neuroimaging data analysis.Journal of the American Statistical Association, 108(502):540–552, 2013

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 04ba70d3-3e0b-4c3a-999e-b78917d12306 · outbound

This paper cites Compressed sensing.IEEE Transactions on information theory, 52(4):1289–1306, 2006.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Compressed sensing.IEEE Transactions on information theory, 52(4):1289–1306, 2006

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd76e9d3-c1ba-416d-a3e1-2d7e35a73aac · outbound

This paper cites Robust uncertainty principles: Exact signal reconstruc- tion from highly incomplete frequency information.IEEE Transactions on information theory, 52(2):489–509, 2006.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Robust uncertainty principles: Exact signal reconstruc- tion from highly incomplete frequency information.IEEE Transactions on information theory, 52(2):489–509, 2006

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d61bb63f-87fc-457b-a66f-6b29522497cf · outbound

This paper cites An introduction to compressive sampling.IEEE signal processing magazine, 25(2):21–30, 2008.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery An introduction to compressive sampling.IEEE signal processing magazine, 25(2):21–30, 2008

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4115f523-bc96-4c5d-9b6c-8800f2c882fa · outbound

This paper cites Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization.SIAM review, 52(3):471–501, 2010.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization.SIAM review, 52(3):471–501, 2010

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e6bf028-d7e5-4645-9e19-f30789f81701 · outbound

This paper cites Iterative hard thresholding for low cp-rank tensor models.Linear and Multilinear Algebra, pages 1–17, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Iterative hard thresholding for low cp-rank tensor models.Linear and Multilinear Algebra, pages 1–17, 2021

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c24b82d0-37bd-42ba-87f2-2ff57a13dade · outbound

This paper cites Modulus of continuity of some conditionally sub-gaussian fields, applica- tion to stable random fields.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Modulus of continuity of some conditionally sub-gaussian fields, applica- tion to stable random fields

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d29f3eb3-ce2f-4368-82e5-538965e26636 · outbound

This paper cites Islet: Fast and optimal low-rank tensor regression via importance sketching.SIAM journal on mathematics of data science, 2(2):444–479, 2020.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Islet: Fast and optimal low-rank tensor regression via importance sketching.SIAM journal on mathematics of data science, 2(2):444–479, 2020

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ccaa2e83-e412-442b-a7d0-ff7d3d05f1dc · outbound

This paper cites A multilinear singular value decomposition.SIAM journal on Matrix Analysis and Applications, 21(4):1253–1278, 2000.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery A multilinear singular value decomposition.SIAM journal on Matrix Analysis and Applications, 21(4):1253–1278, 2000

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7a6a8b24-aeb6-4432-b2a0-dfe77eddc449 · outbound

This paper cites Weakly convex optimization over Stiefel manifold using Riemannian subgradient-type methods.SIAM Journal on Optimization, 31(3):1605–1634, 2021.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Weakly convex optimization over Stiefel manifold using Riemannian subgradient-type methods.SIAM Journal on Optimization, 31(3):1605–1634, 2021

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 42adb768-f63d-4b3c-ba3c-5ab984b5b894 · outbound

This paper cites Springer, 2012.

A Scalable Factorization Approach for High-Order Structured Tensor Recovery Springer, 2012

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 990288e4-fa4c-4166-a80a-871bec443ddb · inbound

Landscape Analysis of Simultaneous Blind Deconvolution and Phase Retrieval via Structured Low-Rank Tensor Recovery cites this paper.

Landscape Analysis of Simultaneous Blind Deconvolution and Phase Retrieval via Structured Low-Rank Tensor Recovery A Scalable Factorization Approach for High-Order Structured Tensor Recovery

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93c86dc8-df28-4e42-9416-10c6308fe686 · inbound

Statistical and Algorithmic Foundations of Probing Quantum Systems with Compressive Measurements: A Review cites this paper.

Statistical and Algorithmic Foundations of Probing Quantum Systems with Compressive Measurements: A Review A Scalable Factorization Approach for High-Order Structured Tensor Recovery

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 176a9092-43e4-4f69-a576-56f1e2c709e7 · inbound

Geometric Analysis of Variational Quantum Eigensolver cites this paper.

Geometric Analysis of Variational Quantum Eigensolver A Scalable Factorization Approach for High-Order Structured Tensor Recovery

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:43:25.756081Z

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Observation 589cd050-c975-4cc1-a465-f387555f4680 · inbound

Structured Adaptive Tensor Prediction for Streaming Data cites this paper.

Structured Adaptive Tensor Prediction for Streaming Data A Scalable Factorization Approach for High-Order Structured Tensor Recovery

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:57:30.432283Z

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Observation b2bacbe3-4877-43e9-9de7-59f3ba9625bc · inbound

A Unified Framework for Sample Complexity of Structured Quantum State Tomography under Noisy Observations cites this paper.

A Unified Framework for Sample Complexity of Structured Quantum State Tomography under Noisy Observations A Scalable Factorization Approach for High-Order Structured Tensor Recovery

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-08T11:38:26.121531Z

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