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Paper Citation Record · LEDGER

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory

As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:1908.03462.

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pith.paper-citation-record.v1
1908.03462 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:22:30.190796Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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External citation measurements

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Outbound references

Observation f5dc4ee2-524b-493e-8763-3c3ec3308222 · outbound

This paper cites an unresolved cited work.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Unresolved cited work

Reference 1

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Observation 29b0f433-8e8d-478e-adba-21212c330b1a · outbound

This paper cites Bhatia, Matrix Analysis , Berlin, Germany: Springer Science & Business Media, 2013.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Bhatia, Matrix Analysis , Berlin, Germany: Springer Science & Business Media, 2013

Reference 2

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This paper cites Signal-plus-noise matri x models: eigenvector deviations and fluctuations,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Signal-plus-noise matri x models: eigenvector deviations and fluctuations,

Reference 3

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This paper cites The Rotation of Eigenvectors by a P er- turbation. III,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory The Rotation of Eigenvectors by a P er- turbation. III,

Reference 4

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This paper cites Spectral Projector-Based Gra ph Fourier Transforms,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Spectral Projector-Based Gra ph Fourier Transforms,

Reference 5

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This paper cites Learning Gra phs from Data: A signal representation perspective,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Learning Gra phs from Data: A signal representation perspective,

Reference 6

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This paper cites The geometry of algo rithms with orthogonality constraints,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory The geometry of algo rithms with orthogonality constraints,

Reference 7

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Observation 6578abf7-fe27-4cde-b96e-e67169fa13a4 · outbound

This paper cites Unperturbed: spectral analysis beyond Davis–Kahan,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Unperturbed: spectral analysis beyond Davis–Kahan,

Reference 8

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This paper cites Large covariance estimati on by thresholding principal orthogonal complements,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Large covariance estimati on by thresholding principal orthogonal complements,

Reference 9

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Unresolved cited work

Reference 10

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Observation 5c322bcc-f055-4d76-be59-e20a82a196e7 · outbound

This paper cites On the distribution of the largest eig envalue in prin- cipal components analysis,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory On the distribution of the largest eig envalue in prin- cipal components analysis,

Reference 11

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Observation afcea7dd-10f0-474d-95c9-6c1f04ad6bab · outbound

This paper cites PCA consistency in High Dimensio n Low Sample Size Context,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory PCA consistency in High Dimensio n Low Sample Size Context,

Reference 12

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This paper cites Graph Similarity based on Graph Fourier Distances,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Graph Similarity based on Graph Fourier Distances,

Reference 13

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Consistency of spectral clusterin g in stochastic block models,

Reference 14

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Observation 8f2f7472-75f0-44d6-abaf-e4ebf43254e0 · outbound

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Unresolved cited work

Reference 15

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Graph Signal Processing: Overview, Challenges, and Appli cations,

Reference 16

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Spectral clustering and the high- dimensional stochastic blockmodel,

Reference 17

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Random perturbation of low rank matrices: Improving classical bounds,

Reference 18

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory First-principles multiwa y spectral partitioning of graphs,

Reference 19

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory The emerging field of signal processing on graphs: Extendin g high- dimensional data analysis to networks and other irregular d omains,

Reference 20

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory On Spectral Anal ysis of Node Centrality,

Reference 21

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Unresolved cited work

Reference 22

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This paper cites Limit Theorems for eigenvectors of the normalized Laplacian for random graphs,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Limit Theorems for eigenvectors of the normalized Laplacian for random graphs,

Reference 23

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory A tutorial on spectral clustering,

Reference 24

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This paper cites Minimax sparse principal subspace est imation in high dimensions,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Minimax sparse principal subspace est imation in high dimensions,

Reference 25

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Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Asymptotics of empirical eigenstruct ure for high dimensional spiked covariance,

Reference 26

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Source-reported events for the cited work

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This paper cites Integration of network topological features and graph Fou rier transform for fMRI data analysis,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory Integration of network topological features and graph Fou rier transform for fMRI data analysis,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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This paper cites A useful variant of the Da vis–Kahan theorem for statisticians,.

Extending the Davis-Kahan theorem for comparing eigenvectors of two symmetric matrices I: Theory A useful variant of the Da vis–Kahan theorem for statisticians,

Reference 28

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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 2026-08-16T06:30:59.297886+00:00.

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