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Paper Citation Record · LEDGER

Lasso and Partially-Rotated Designs

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.11093.

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

pith.paper-citation-record.v1
2505.11093 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:17:18.108977Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

32 of 32 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e9d8bb96-0a43-46bd-ab61-aec3ecdb4ba7 · outbound

This paper cites Adamczak, A.

Lasso and Partially-Rotated Designs Adamczak, A

Reference 1

Resolution
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Source-reported events for the cited work

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Observation fc9605b5-bfea-42ea-ab45-1fe3a84575fd · outbound

This paper cites Bickel, Ya'acov Ritov, and Alexandre B.

Lasso and Partially-Rotated Designs Bickel, Ya'acov Ritov, and Alexandre B

Reference 2

Resolution
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Source-reported events for the cited work

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Observation ebaad2af-4459-4298-860e-13db59cbe39e · outbound

This paper cites Correlated variables in regression: Clustering and sparse estimation.

Lasso and Partially-Rotated Designs Correlated variables in regression: Clustering and sparse estimation

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 6e2c0cfc-ae95-4f79-b2fe-a0be272fbd78 · outbound

This paper cites Candes and Terence Tao.

Lasso and Partially-Rotated Designs Candes and Terence Tao

Reference 4

Resolution
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Source-reported events for the cited work

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Observation 6c08217c-edc8-4a85-836a-d650604548ed · outbound

This paper cites Consistent estimation for pca and sparse regression with oblivious outliers.

Lasso and Partially-Rotated Designs Consistent estimation for pca and sparse regression with oblivious outliers

Reference 5

Resolution
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Source-reported events for the cited work

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Observation 28f3599c-dce9-4684-a555-9975adaed1f9 · outbound

This paper cites Outlier-robust estimation of a sparse linear model using l1-penalized huber's m-estimator.

Lasso and Partially-Rotated Designs Outlier-robust estimation of a sparse linear model using l1-penalized huber's m-estimator

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 8a1dee3c-e6f2-466c-9138-6b3d3a809777 · outbound

This paper cites Ordered weighted l1 regularized regression with strongly correlated covariates: Theoretical aspects.

Lasso and Partially-Rotated Designs Ordered weighted l1 regularized regression with strongly correlated covariates: Theoretical aspects

Reference 7

Resolution
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Source-reported events for the cited work

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Observation 0f937f57-6d8c-42c7-8f8b-e53f0aa63ceb · outbound

This paper cites Variable selection through correlation sifting.

Lasso and Partially-Rotated Designs Variable selection through correlation sifting

Reference 8

Resolution
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Source-reported events for the cited work

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Observation a9df60c6-170f-43ef-9873-4608ff1877a3 · outbound

This paper cites On the power of preconditioning in sparse linear regression.

Lasso and Partially-Rotated Designs On the power of preconditioning in sparse linear regression

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 291b6f68-4603-4020-bc78-7ecf85b7a821 · outbound

This paper cites Feature adaptation for sparse linear regression.

Lasso and Partially-Rotated Designs Feature adaptation for sparse linear regression

Reference 10

Resolution
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Source-reported events for the cited work

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Observation 0cd2fb7e-7b90-4cfb-bb84-178a7c91a236 · outbound

This paper cites Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps.

Lasso and Partially-Rotated Designs Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps

Reference 11

Resolution
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Observation 942db6c3-8166-4039-9d8c-9d8d6e8947f9 · outbound

This paper cites Semi-random sparse recovery in nearly-linear time.

Lasso and Partially-Rotated Designs Semi-random sparse recovery in nearly-linear time

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 059d1c02-b381-47e7-b6b1-39bcc97727db · outbound

This paper cites Compressed Sensing with Adversarial Sparse Noise via L1 Regression.

Lasso and Partially-Rotated Designs Compressed Sensing with Adversarial Sparse Noise via L1 Regression

Reference 13

Resolution
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Source-reported events for the cited work

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This paper cites Sparse recovery under weak moment assumptions.

Lasso and Partially-Rotated Designs Sparse recovery under weak moment assumptions

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1ac8ea9f-5647-407b-a6fd-e6afa0114437 · outbound

This paper cites Graph-based regularization for regression problems with highly-correlated designs.

Lasso and Partially-Rotated Designs Graph-based regularization for regression problems with highly-correlated designs

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Lasso and Partially-Rotated Designs High dimensional robust sparse regression

Reference 16

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Uniform uncertainty principle for B ernoulli and subgaussian ensembles

Reference 17

Resolution
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Source-reported events for the cited work

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Observation eade9561-32fd-45df-875d-49a590280b57 · outbound

This paper cites Negahban, Pradeep Ravikumar, Martin J.

Lasso and Partially-Rotated Designs Negahban, Pradeep Ravikumar, Martin J

Reference 18

Resolution
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Source-reported events for the cited work

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Observation 0475e9be-07cc-4d48-be6f-03ab9952aa35 · outbound

This paper cites The lower tail of random quadratic forms with applications to ordinary least squares.

Lasso and Partially-Rotated Designs The lower tail of random quadratic forms with applications to ordinary least squares

Reference 19

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Maurey-Schwartz

Reference 20

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Source-reported events for the cited work

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Observation 5de5d709-228e-40e3-baa3-fb5e1be65dc3 · outbound

This paper cites On sparse reconstruction from F ourier and G aussian measurements.

Lasso and Partially-Rotated Designs On sparse reconstruction from F ourier and G aussian measurements

Reference 21

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Hanson- W right inequality and sub- G aussian concentration

Reference 22

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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Wainwright, and Bin Yu

Reference 23

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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Wainwright, and Bin Yu

Reference 24

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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Reconstruction from anisotropic random measurements

Reference 25

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Regression shrinkage and selection via the lasso

Reference 26

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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs u r Statistik, Eidgen \

Reference 27

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs van de Geer and Peter B\" u hlmann

Reference 28

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 29

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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Wainwright

Reference 30

Resolution
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Source-reported events for the cited work

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Observation 17e07026-5fc7-4318-9669-4745266abbc4 · outbound

This paper cites A comparative framework for preconditioned lasso algorithms.

Lasso and Partially-Rotated Designs A comparative framework for preconditioned lasso algorithms

Reference 31

Resolution
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Source-reported events for the cited work

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Lasso and Partially-Rotated Designs Regularization and variable selection via the elastic net

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Pith citing papers

No inbound Pith citation observations are available.