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Paper Citation Record · LEDGER

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

As of 13 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 8 inbound Pith citation observations for arXiv:2501.09336.

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

pith.paper-citation-record.v1
2501.09336 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:12:54.047307Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:15:29.045601Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy22
  • unresolved6
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 69bb508d-a054-4246-9e47-44dad14f9e3d · outbound

This paper cites Spectral methods for data science: A statistical perspective.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Spectral methods for data science: A statistical perspective

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 76df8573-203f-4bd7-97cb-9406e78a2fed · outbound

This paper cites Vincent Poor, and Yuxin Chen.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Vincent Poor, and Yuxin Chen

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.893781Z digest=sha256:347692f9ec13b7d66bcbdac47ec05f89605d7076d50f2dd2dec75226e6eaf76d

Observation dd348f25-6142-4644-b532-a0a2eadf278e · outbound

This paper cites Tony Cai, Zongming Ma, and Yihong Wu.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Tony Cai, Zongming Ma, and Yihong Wu

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9927aca6-7df7-4e56-8345-33ba7db01583 · outbound

This paper cites Tony Cai and Anru Zhang.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Tony Cai and Anru Zhang

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.903412Z digest=sha256:ff7c6f21b3826e521c9179e969f6a34dead7bd5903216d4e04c1fda433af618a

Observation 2d21b56a-75c8-429b-9892-a8c89d5b84ce · outbound

This paper cites Detection limits in the high-dimensional spiked rectangular model.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Detection limits in the high-dimensional spiked rectangular model

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fa2f5ba6-45cd-4df5-b943-22328aed1eb4 · outbound

This paper cites Angle-based joint and individual variation explained.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Angle-based joint and individual variation explained

Reference 6

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.913563Z digest=sha256:87110db2ec834ca7c5bbf07c7c585007b35141aaa28465718837a5bda13d3f84

Observation 92af1363-bb96-4146-b931-a2dae20fae17 · outbound

This paper cites Distributed estimation of principal eigenspaces.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Distributed estimation of principal eigenspaces

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.917828Z digest=sha256:e9743bab8a90478097baa93ebdf6bc16b437c2c0652707637d3c9a0976e44ede

Observation f5569ee1-5563-4863-97ac-51eb7113ba82 · outbound

This paper cites Structural learning and integrative decomposition of multi-view data.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Structural learning and integrative decomposition of multi-view data

Reference 8

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 006a48ed-b17d-4fb5-9b4b-96a24ab2455c · outbound

This paper cites Covariate-driven factorization by thresholding for multiblock data.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Covariate-driven factorization by thresholding for multiblock data

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 627398e6-af42-4e72-8130-08ec57992dd9 · outbound

This paper cites On a formula for the product-moment coefficient of any order of a normal frequency distribution in any number of variables.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices On a formula for the product-moment coefficient of any order of a normal frequency distribution in any number of variables

Reference 10

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b412c692-04dd-4c76-b41d-c1d71255547a · outbound

This paper cites Information and coding theory.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Information and coding theory

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.936880Z digest=sha256:d45baaa85ad9418d81bac7719f45961dfa3661ff4a9b71564162aec319d14b9e

Observation 0faf55c2-9afa-47d2-b94b-0a976bb44ef8 · outbound

This paper cites The incidental parameter problem since 1948.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices The incidental parameter problem since 1948

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 05b1c3ed-fc20-447f-b9a3-03f5225dde65 · outbound

This paper cites Joint and individual variation explained ( JIVE ) for integrated analysis of multiple data types.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Joint and individual variation explained ( JIVE ) for integrated analysis of multiple data types

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0331b1d8-983e-473f-907d-79e37bc48f1c · outbound

This paper cites an unresolved cited work.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7c6b740e-9811-49ab-9fb0-b225f9e78864 · outbound

This paper cites Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:12:53.962964Z digest=sha256:5a64b2320d41d9a41e38b00589d51f6076d96ebd90233a2044e57c78a63e0bf4

Observation 12978f7c-05c8-4009-a744-c4a62978f7c8 · outbound

This paper cites Consistent estimates based on partially consistent observations.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Consistent estimates based on partially consistent observations

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.969003Z digest=sha256:cd947f1120987cb07dbf9cc3304dc9ba215d7f86d6e3549ec2ef2d7477c21454

Observation 1c1c0119-b755-4822-8b13-499bb9acc233 · outbound

This paper cites Fourth-order properties of normally distributed random matrices.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Fourth-order properties of normally distributed random matrices

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 14ef5564-ac09-4d3d-8e59-9d660331110f · outbound

This paper cites Data integration via analysis of subspaces ( DIVAS ).

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Data integration via analysis of subspaces ( DIVAS )

Reference 18

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.977603Z digest=sha256:07d18d96107f437fe835de9ca42b4cc07147dce75b082daf56f3e33df8fe79a8

Observation 92af24f6-01c6-45f1-87ab-0bbd8f9b83d6 · outbound

This paper cites RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data

Reference 19

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local_arxiv, observed 2026-08-10T20:12:54.332795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.982162Z digest=sha256:61c82e27be7d2626bc1c102a92fa88096e25449148c90ac861b75e5a0d332695

Observation 36f32722-2104-47f8-b461-7210a57fa057 · outbound

This paper cites Triple component matrix factorization: Untangling global, local, and noisy components.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Triple component matrix factorization: Untangling global, local, and noisy components

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-10T20:12:54.467058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-10T20:12:53.987930Z digest=sha256:4af0ea8d4817f160aaa8ddb12a32f1c9b138d0c259fb13aadfcb3aa021205035

Observation a05ae711-37f7-4d09-ac57-414fc67f2b8e · outbound

This paper cites Personalized PCA : Decoupling shared and unique features.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Personalized PCA : Decoupling shared and unique features

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7772ac74-ed13-4f29-960d-f0dd838e0b92 · outbound

This paper cites Heterogeneous Matrix Factorization: When Features Differ by Datasets.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Heterogeneous Matrix Factorization: When Features Differ by Datasets

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:12:54.000118Z digest=sha256:e586c98b76c046915012eb313266e9f7b3711eea3f29bed9face9352d74de099

Observation c096f2bf-54d9-452f-ab0e-537c58778333 · outbound

This paper cites A spectral method for multi-view subspace learning using the product of projections.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices A spectral method for multi-view subspace learning using the product of projections

Reference 23

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no resolver link, observed 2026-08-10T20:12:54.007851Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:12:54.007851Z digest=sha256:d8a276b9918461d20ceb68979da8e4d87bf424349a33a689f026e0c0037ea6ef

Observation a8d263e4-bf50-4694-b039-fc94b6b15d66 · outbound

This paper cites High-dimensional probability: An introduction with applications in data science , volume 47.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices High-dimensional probability: An introduction with applications in data science , volume 47

Reference 24

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no resolver link, observed 2026-08-10T20:12:54.014100Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:12:54.014100Z digest=sha256:2d87372aa9f7b34853358c11b67c51555ecf5df92d9a63d0bc54626df3f83412

Observation b784c5c2-1c52-4ab9-ad1d-5e1200dfd1f0 · outbound

This paper cites Perturbation theory for pseudo-inverses.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Perturbation theory for pseudo-inverses

Reference 25

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 616d9059-7f8b-493e-b423-879ac994d32b · outbound

This paper cites Normal approximation and confidence region of singular subspaces.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Normal approximation and confidence region of singular subspaces

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation f4202637-1d88-413e-a112-789cfc6dec2c · outbound

This paper cites Assouad, F ano, and L e C am.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Assouad, F ano, and L e C am

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-10T20:12:54.387439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fed184a7-89c2-49ca-b3eb-49c773850231 · outbound

This paper cites Group component analysis for multiblock data: Common and individual feature extraction.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Group component analysis for multiblock data: Common and individual feature extraction

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-10T20:12:54.369494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation db7ca027-870a-4e48-b320-60648d1dbf7f · outbound

This paper cites Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA.

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA

Reference 29

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T20:12:54.047307Z digest=sha256:201ff0189d33246ae4d3fa53d128e797425992eaa35347a62407aefc25084f4c

Pith citing papers

Observation 624e8f3b-cf4a-4ec7-a56d-99a62ec1d567 · inbound

Stacked SVD or SVD stacked? A Random Matrix Theory perspective on data integration cites this paper.

Stacked SVD or SVD stacked? A Random Matrix Theory perspective on data integration Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 52

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unresolved
no resolver link, observed 2026-08-06T12:15:29.045601Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:15:29.045601Z digest=sha256:79554783ecc26b92ca82153747b7540a8fa332f4fc2fe10dca6d1a9e64443216

Observation 9906e1a0-cfd9-4654-9f3d-f73215e3e662 · inbound

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation cites this paper.

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 13

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verified exact
arxiv_id, observed 2026-05-18T18:31:44.051574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5d925c0e-360d-41c1-b53c-035a941c9fcc · inbound

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation cites this paper.

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 2022

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:35:15.177522Z digest=sha256:771170fe0732146fb930007038eb3001b76fb411436014e2354a9c754ab14f6d

Observation 83082cdc-f666-43c5-b074-a7904a7239fe · inbound

Spectral Joint Subspace Estimation for Heterogeneous Multi-View Data: Geometry and Reweighting cites this paper.

Spectral Joint Subspace Estimation for Heterogeneous Multi-View Data: Geometry and Reweighting Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 2024

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:02:27.962581Z digest=sha256:17b28f40bf5141e51ee718fba13df4b22f9a2b1a4b6dd212438e90eeb54090f0

Observation e53b7a83-ad94-4dd0-a0bc-ec5634835231 · inbound

Statistically and Computationally Optimal Estimation and Inference of Common Subspaces cites this paper.

Statistically and Computationally Optimal Estimation and Inference of Common Subspaces Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 59

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arxiv_id, observed 2026-06-27T23:11:22.730180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T23:11:05.443406Z digest=sha256:2101a09ee5d34b0cb72295a5716cfcd9f9a435225fc4b9562eb308484764356d

Observation 4733182a-428d-45b6-a7b9-b2b377bad55d · inbound

Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records cites this paper.

Enhancing Spectral Embedding through Robust and Flexible Knowledge Transfer in Electronic Health Records Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T12:58:08.642656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T08:35:37.953328Z digest=sha256:f8c7de08ba80a4a5bbce2bf6fdaf83f79b39f6876369d6daf22d5e3e974120f3

Observation c395e63d-5d5c-4ec4-993b-70680c41ef94 · inbound

Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS cites this paper.

Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-01T15:46:35.747882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T15:46:35.747882Z digest=sha256:9cd220d35651b89dba3e6de29f48229b404b9d16bce3fbab23281ad72c15a857

Observation 3314d95c-ca82-455a-b453-1237ff329649 · inbound

Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data cites this paper.

Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices

Reference 62

Resolution
unresolved
no resolver link, observed 2026-07-31T03:15:47.986731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T03:15:47.986731Z digest=sha256:98ac5f8cfa2eb4160f0f8c8132d03885d814223437098925466619755930173d