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Paper Citation Record · LEDGER

On the Adversarial Robustness of Subspace Learning

As of 16 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:1908.06210.

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

pith.paper-citation-record.v1
1908.06210 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:02:34.478313Z

measured 34 of 34 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

34 of 34 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 82cd57b4-01db-44e2-8fe5-b3977fc43fc1 · outbound

This paper cites On the adversarial robustness o f subspace learning,.

On the Adversarial Robustness of Subspace Learning On the adversarial robustness o f subspace learning,

Reference 1

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Observation 4654992a-3355-4cce-b542-8d72c8961ea5 · outbound

This paper cites Structure d sparse representation with union of data-driven linear and multil inear subspaces model for compressive video sampling,.

On the Adversarial Robustness of Subspace Learning Structure d sparse representation with union of data-driven linear and multil inear subspaces model for compressive video sampling,

Reference 2

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Observation f5ea69cd-b499-4358-bf46-5229a5883b4e · outbound

This paper cites Subspace-based adaptive m ethod for estimating direction-of-arrival with luenberger observe r,.

On the Adversarial Robustness of Subspace Learning Subspace-based adaptive m ethod for estimating direction-of-arrival with luenberger observe r,

Reference 3

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Observation cebd7ecb-f944-497e-a1f6-72a33f94e122 · outbound

This paper cites Online categor ical subspace learning for sketching big data with misses,.

On the Adversarial Robustness of Subspace Learning Online categor ical subspace learning for sketching big data with misses,

Reference 4

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Observation c9388a38-a2ac-416f-90a0-a3bd7b92b499 · outbound

This paper cites An online algorithm for se parating sparse and low-dimensional signal sequences from their sum ,.

On the Adversarial Robustness of Subspace Learning An online algorithm for se parating sparse and low-dimensional signal sequences from their sum ,

Reference 5

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Observation c7b4f34d-a136-4898-b36d-dbea95ededf8 · outbound

This paper cites Low-rank pl us sparse matrix decomposition for accelerated dynamic MRI with sepa ration of background and dynamic components,.

On the Adversarial Robustness of Subspace Learning Low-rank pl us sparse matrix decomposition for accelerated dynamic MRI with sepa ration of background and dynamic components,

Reference 6

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Observation 210b77a4-735e-4c7b-9efb-cb8a05704944 · outbound

This paper cites Matrix factorizatio n techniques for recommender systems,.

On the Adversarial Robustness of Subspace Learning Matrix factorizatio n techniques for recommender systems,

Reference 7

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Observation 55ef856c-5761-4c93-9837-bb5c1744135d · outbound

This paper cites Dynamic anom alog- raphy: Tracking network anomalies via sparsity and low rank ,.

On the Adversarial Robustness of Subspace Learning Dynamic anom alog- raphy: Tracking network anomalies via sparsity and low rank ,

Reference 8

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Observation f651f88c-ae29-425c-842e-d7cc74f1e210 · outbound

This paper cites Video denoising via online sparse and low- rank matrix decomposition,.

On the Adversarial Robustness of Subspace Learning Video denoising via online sparse and low- rank matrix decomposition,

Reference 9

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Observation 3a5129c8-6f42-4aed-83e4-fe7244226448 · outbound

This paper cites Robust princi pal component analysis?.

On the Adversarial Robustness of Subspace Learning Robust princi pal component analysis?

Reference 10

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Observation 55977c37-c2ba-4bde-ba7b-db57108de70d · outbound

This paper cites Robust matrix decomp osition with sparse corruptions,.

On the Adversarial Robustness of Subspace Learning Robust matrix decomp osition with sparse corruptions,

Reference 11

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Observation 2acab2dc-60db-499f-9ec3-59ae60482838 · outbound

This paper cites Recursive ro bust PCA or recursive sparse recovery in large but structured noi se,.

On the Adversarial Robustness of Subspace Learning Recursive ro bust PCA or recursive sparse recovery in large but structured noi se,

Reference 12

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Observation 0b7f1c7a-a222-43e0-a9b4-91b769e3874a · outbound

This paper cites Robust ma trix completion and corrupted columns,.

On the Adversarial Robustness of Subspace Learning Robust ma trix completion and corrupted columns,

Reference 13

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Observation c7591962-906d-4f03-90a3-7fb221b197ae · outbound

This paper cites Robust Physical-World Attacks on Deep Learning Models.

On the Adversarial Robustness of Subspace Learning Robust Physical-World Attacks on Deep Learning Models

Reference 14

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Source-reported events for the cited work

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Observation 371b0273-2d50-4f5b-8b83-96f1bd8b9d5e · outbound

This paper cites Hidden voice commands,.

On the Adversarial Robustness of Subspace Learning Hidden voice commands,

Reference 15

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Source-reported events for the cited work

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Observation b741b252-99a1-493c-82f5-1a607205416b · outbound

This paper cites Adversarial attacks on medical machine learning,.

On the Adversarial Robustness of Subspace Learning Adversarial attacks on medical machine learning,

Reference 16

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Source-reported events for the cited work

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Observation fd157970-f261-4885-9688-8e2dbf8d7c3c · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

On the Adversarial Robustness of Subspace Learning Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 17

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Source-reported events for the cited work

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Observation fa8e9392-ab5a-48b5-bceb-f860fe94c40a · outbound

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On the Adversarial Robustness of Subspace Learning Unresolved cited work

Reference 18

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Observation 90662f66-beeb-464d-a290-bdbed77272ee · outbound

This paper cites The geometry of algorithms with orthogonality constraints,.

On the Adversarial Robustness of Subspace Learning The geometry of algorithms with orthogonality constraints,

Reference 19

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Source-reported events for the cited work

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Observation 7569839a-724c-4266-8f46-8a967b136451 · outbound

This paper cites Almost invariant submanifolds for comp act group ac- tions,.

On the Adversarial Robustness of Subspace Learning Almost invariant submanifolds for comp act group ac- tions,

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 24d94bde-d93d-4bda-a9a5-c862de362336 · outbound

This paper cites Optimal robustness in th e gap metric,.

On the Adversarial Robustness of Subspace Learning Optimal robustness in th e gap metric,

Reference 21

Resolution
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Observation 15e3ee25-848d-482c-8ea6-8e1a5c5c2fb7 · outbound

This paper cites Frequency domain uncertainty and the g raph topology,.

On the Adversarial Robustness of Subspace Learning Frequency domain uncertainty and the g raph topology,

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 553211f1-d8e1-4b71-a49c-631b8a4e165c · outbound

This paper cites Feedback stability under simult aneous gap metric uncertainties in plant and controller,.

On the Adversarial Robustness of Subspace Learning Feedback stability under simult aneous gap metric uncertainties in plant and controller,

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 6325630f-beeb-416a-a7ca-bea1c3b56e11 · outbound

This paper cites Manipulating machine learning: Poisoning attacks and cou ntermeasures for regression learning,.

On the Adversarial Robustness of Subspace Learning Manipulating machine learning: Poisoning attacks and cou ntermeasures for regression learning,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 6961d8a2-9078-4cdd-bcdf-7be287892d7f · outbound

This paper cites On the Adversarial Robustness of Multivariate Robust Estimation.

On the Adversarial Robustness of Subspace Learning On the Adversarial Robustness of Multivariate Robust Estimation

Reference 25

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Observation 7787afa8-f572-4cec-8494-788eef798c0e · outbound

This paper cites Adversarial principal component analysis,.

On the Adversarial Robustness of Subspace Learning Adversarial principal component analysis,

Reference 26

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Source-reported events for the cited work

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Observation e1bb8241-5858-4a19-a666-0fa357343fba · outbound

This paper cites The role of princip al angles in subspace classification,.

On the Adversarial Robustness of Subspace Learning The role of princip al angles in subspace classification,

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 09d4ce3e-a5df-46c0-97e4-ddc776e62cbc · outbound

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On the Adversarial Robustness of Subspace Learning Robust detection with the gap metr ic,

Reference 28

Resolution
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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Observation b581e294-d583-44b5-b1ce-8be23d997b85 · outbound

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On the Adversarial Robustness of Subspace Learning On the largest prin cipal angle between random subspaces,

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 624f616c-2730-499f-835c-f12efacc28c8 · outbound

This paper cites A geometric note on subspace updates and orthogonal matrix decompositions under rank-one modifications.

On the Adversarial Robustness of Subspace Learning A geometric note on subspace updates and orthogonal matrix decompositions under rank-one modifications

Reference 30

Resolution
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Source-reported events for the cited work

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Observation f4a90d5d-874a-401b-a034-e19e90a7a168 · outbound

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On the Adversarial Robustness of Subspace Learning Unresolved cited work

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 77989e91-b3f2-43bc-86e9-3fabb3d50191 · outbound

This paper cites The behavior of eigenvalues and singul ar values under perturbations of restricted rank,.

On the Adversarial Robustness of Subspace Learning The behavior of eigenvalues and singul ar values under perturbations of restricted rank,

Reference 32

Resolution
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Source-reported events for the cited work

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Observation d8b93ee6-36ba-4dce-bfa5-fac73bf6d5c0 · outbound

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On the Adversarial Robustness of Subspace Learning Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation 1dfa00ce-0f87-430d-8446-ea333d513ed4 · outbound

This paper cites Two data sets of near infrared spectra,.

On the Adversarial Robustness of Subspace Learning Two data sets of near infrared spectra,

Reference 34

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Source-reported events for the cited work

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Pith citing papers

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