Paper Citation Record · LEDGER

Debiasing the Lasso under Weaker Tail Assumptions

As of 19 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2608.04800.

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pith.paper-citation-record.v1
2608.04800 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:47:18.707089Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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unresolved36
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Outbound references

Observation b9186836-5c6e-44e3-8650-8b9026b7108a · outbound

This paper cites Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer.Ann Appl Stat, 4(1):53–77, March 2010.

Debiasing the Lasso under Weaker Tail Assumptions Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer.Ann Appl Stat, 4(1):53–77, March 2010

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.516597Z

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Observation 1b3cc9f5-5b6d-457e-8901-f8a7c8cc8b61 · outbound

This paper cites High-dimensional statistics, with applications to genome-wide association studies.EMS Surv.

Debiasing the Lasso under Weaker Tail Assumptions High-dimensional statistics, with applications to genome-wide association studies.EMS Surv

Reference 2

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Observation a3200db3-bb05-4513-b379-7fa3c0bcfd9b · outbound

This paper cites Improving genomic prediction using High-Dimensional secondary phenotypes: The genetic latent factor approach.Biom J, 67(5):e70081, October 2025.

Debiasing the Lasso under Weaker Tail Assumptions Improving genomic prediction using High-Dimensional secondary phenotypes: The genetic latent factor approach.Biom J, 67(5):e70081, October 2025

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.530379Z

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Observation 96a513de-42f7-447c-91a4-5103fd9e92e9 · outbound

This paper cites Sparse discriminant analysis.Technomet- rics, 53(4):406–413, 2011.

Debiasing the Lasso under Weaker Tail Assumptions Sparse discriminant analysis.Technomet- rics, 53(4):406–413, 2011

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.535517Z

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Observation 1688817e-d248-4c61-8707-282a5c9062f5 · outbound

This paper cites Variableselectionusingrandomforests.Pattern Recognition Letters, 31(14):2225–2236, 2010.

Debiasing the Lasso under Weaker Tail Assumptions Variableselectionusingrandomforests.Pattern Recognition Letters, 31(14):2225–2236, 2010

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.540825Z

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Observation 697a861a-313f-4bd2-b32c-290bc5a1da09 · outbound

This paper cites Handling high-dimensional data with missing values by modern machine learning techniques.J Appl Stat, 50(3):786–804, May 2022.

Debiasing the Lasso under Weaker Tail Assumptions Handling high-dimensional data with missing values by modern machine learning techniques.J Appl Stat, 50(3):786–804, May 2022

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.546358Z

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Observation bb0028d8-056d-4ad3-b9b0-923b98819ee1 · outbound

This paper cites Robust high dimensional factor models with applications to statistical machine learning.Stat Sci, 36(2):303–327, April 2021.

Debiasing the Lasso under Weaker Tail Assumptions Robust high dimensional factor models with applications to statistical machine learning.Stat Sci, 36(2):303–327, April 2021

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.552520Z

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Observation 7e97eb67-f73e-4351-b36a-81d2a356d8df · outbound

This paper cites Inference on treatment effects after selection among high-dimensional controls†.The Review of Economic Studies, 81(2):608–650, 04 2014.

Debiasing the Lasso under Weaker Tail Assumptions Inference on treatment effects after selection among high-dimensional controls†.The Review of Economic Studies, 81(2):608–650, 04 2014

Reference 8

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Observation 7bfc7e36-8c4c-4f51-8b1a-511ec7b9298a · outbound

This paper cites Sparsemodelsandmethodsforoptimalinstrumentswith an application to eminent domain.Econometrica, 80(6):2369–2429, 2012.

Debiasing the Lasso under Weaker Tail Assumptions Sparsemodelsandmethodsforoptimalinstrumentswith an application to eminent domain.Econometrica, 80(6):2369–2429, 2012

Reference 9

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Observation 16be357f-4d4a-483c-ac4b-9701c2af469e · outbound

This paper cites High-dimensional methods and inference on structural and treatment effects.Journal of Economic Perspectives, 28(2):29–50, May 2014.

Debiasing the Lasso under Weaker Tail Assumptions High-dimensional methods and inference on structural and treatment effects.Journal of Economic Perspectives, 28(2):29–50, May 2014

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.568482Z

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Observation f0a99676-6699-4623-9ed8-f9dc2b6bf8d9 · outbound

This paper cites Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society: Series B (Methodological), 58(1):267–288, 12 2018.

Debiasing the Lasso under Weaker Tail Assumptions Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society: Series B (Methodological), 58(1):267–288, 12 2018

Reference 11

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Observation acaa67e2-2ed5-46bc-b83c-d6b183a1127a · outbound

This paper cites an unresolved cited work.

Debiasing the Lasso under Weaker Tail Assumptions Unresolved cited work

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.579677Z

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Observation fab10994-2217-4dc4-b0e9-f0a5ebc76c6e · outbound

This paper cites On asymptotically optimal confidence regions and tests for high-dimensional models.The Annals of Statistics, 42(3):1166–1202, 2014.

Debiasing the Lasso under Weaker Tail Assumptions On asymptotically optimal confidence regions and tests for high-dimensional models.The Annals of Statistics, 42(3):1166–1202, 2014

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.585295Z

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Observation f2acfa19-ae4d-4fba-9a05-3c6b9acc0f6b · outbound

This paper cites Confidence intervals and hypothesis testing for high-dimensional regression.Journal of Machine Learning Research, 15(82):2869–2909, 2014.

Debiasing the Lasso under Weaker Tail Assumptions Confidence intervals and hypothesis testing for high-dimensional regression.Journal of Machine Learning Research, 15(82):2869–2909, 2014

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.590295Z

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Observation 3c19e71c-e06c-465b-8249-d1f1d1bc0ce5 · outbound

This paper cites Debiasing the debiased Lasso with bootstrap.Electronic Journal of Statistics, 14(1):2298 – 2337, 2020.

Debiasing the Lasso under Weaker Tail Assumptions Debiasing the debiased Lasso with bootstrap.Electronic Journal of Statistics, 14(1):2298 – 2337, 2020

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.595798Z

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Observation 057a0c24-20c3-413d-83c3-723cceac33e4 · outbound

This paper cites Bellec and Cun-Hui Zhang.

Debiasing the Lasso under Weaker Tail Assumptions Bellec and Cun-Hui Zhang

Reference 16

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Observation aa3dd7c1-8e16-4ecb-9517-dd83902449bd · outbound

This paper cites Debiasing the lasso: Optimal sample size for Gaussian designs.The Annals of Statistics, 46(6A):2593 – 2622, 2018.

Debiasing the Lasso under Weaker Tail Assumptions Debiasing the lasso: Optimal sample size for Gaussian designs.The Annals of Statistics, 46(6A):2593 – 2622, 2018

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.606498Z

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Observation 9100075f-1f91-4ca0-bfec-167497ab017b · outbound

This paper cites High-dimensionalinferenceforgeneralizedlinearmodelswith hidden confounding.J.

Debiasing the Lasso under Weaker Tail Assumptions High-dimensionalinferenceforgeneralizedlinearmodelswith hidden confounding.J

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.611621Z

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Observation f41d45e6-68bf-4dc8-af03-5aae5f7aa2f9 · outbound

This paper cites Debiasedlassoforgeneralizedlinearmodelswithadivergingnumberofcovariates.

Debiasing the Lasso under Weaker Tail Assumptions Debiasedlassoforgeneralizedlinearmodelswithadivergingnumberofcovariates

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.616526Z

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Observation e2f2f99d-2637-410d-b60a-b205acecbeb4 · outbound

This paper cites Confidence intervals for high-dimensional inverse covariance estimation.

Debiasing the Lasso under Weaker Tail Assumptions Confidence intervals for high-dimensional inverse covariance estimation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.621162Z

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Observation fe67fc23-527d-49d7-a145-ab4c8cfcffaa · outbound

This paper cites Statistical inference on high-dimensional covariate-dependent gaussian graphical regressions.Biometrics, 81(4), October 2025.

Debiasing the Lasso under Weaker Tail Assumptions Statistical inference on high-dimensional covariate-dependent gaussian graphical regressions.Biometrics, 81(4), October 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.626271Z

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Observation 169b6e59-b697-418c-983c-28cee2098312 · outbound

This paper cites Ageneraltheoryofhypothesistestsandconfidenceregionsforsparsehighdimensional models.The Annals of Statistics, 45(1):158 – 195, 2017.

Debiasing the Lasso under Weaker Tail Assumptions Ageneraltheoryofhypothesistestsandconfidenceregionsforsparsehighdimensional models.The Annals of Statistics, 45(1):158 – 195, 2017

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.631354Z

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Observation ab68350d-3088-4e63-83b2-945fbc5f52ae · outbound

This paper cites Probability and Its Applications (New York).

Debiasing the Lasso under Weaker Tail Assumptions Probability and Its Applications (New York)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.635939Z

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Observation 498ed199-e5c7-4cf9-b4f1-c784fcd99930 · outbound

This paper cites Oxford University Press, 02 2013.

Debiasing the Lasso under Weaker Tail Assumptions Oxford University Press, 02 2013

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.640848Z

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Observation 10ab2a6b-4002-4ec2-8823-3c113f513669 · outbound

This paper cites an unresolved cited work.

Debiasing the Lasso under Weaker Tail Assumptions Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.646451Z

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Observation f3cc8322-407c-4004-96b9-fda28a49c534 · outbound

This paper cites Stable recovery of sparse signals and an oracle inequality.IEEE Trans.

Debiasing the Lasso under Weaker Tail Assumptions Stable recovery of sparse signals and an oracle inequality.IEEE Trans

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.651962Z

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Observation 61ffa7e1-bd4c-4a4f-82d1-cf8767edd71c · outbound

This paper cites an unresolved cited work.

Debiasing the Lasso under Weaker Tail Assumptions Unresolved cited work

Reference 27

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Observation f8de80d6-ddf7-4166-ade7-848db498e88a · outbound

This paper cites The Dantzig selector: Statistical estimation when p is much larger than n.

Debiasing the Lasso under Weaker Tail Assumptions The Dantzig selector: Statistical estimation when p is much larger than n

Reference 28

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Observation 3a67919b-30f0-4296-a79e-81d35d9565c3 · outbound

This paper cites SimultaneousanalysisofLassoandDantzigselector.

Debiasing the Lasso under Weaker Tail Assumptions SimultaneousanalysisofLassoandDantzigselector

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.667245Z

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Observation 5c0e7d98-2760-4d48-a52a-fc626020b968 · outbound

This paper cites OntheconditionsusedtoproveoracleresultsfortheLasso.Electronic Journal of Statistics, 3(none):1360 – 1392, 2009.

Debiasing the Lasso under Weaker Tail Assumptions OntheconditionsusedtoproveoracleresultsfortheLasso.Electronic Journal of Statistics, 3(none):1360 – 1392, 2009

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.673131Z

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Observation 9de51356-bbda-4732-b9a5-719b471365cc · outbound

This paper cites Thelowertailofrandomquadraticformswithapplicationstoordinaryleastsquares.

Debiasing the Lasso under Weaker Tail Assumptions Thelowertailofrandomquadraticformswithapplicationstoordinaryleastsquares

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.678401Z

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Observation b7a95a59-92d5-4458-9666-a1911aabf369 · outbound

This paper cites Tony Cai and Zijian Guo.

Debiasing the Lasso under Weaker Tail Assumptions Tony Cai and Zijian Guo

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.683607Z

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Observation 5fd782f9-9a2c-4dda-afda-ee557e938d84 · outbound

This paper cites A remark on moment-dependent phase transitions in high- dimensional gaussian approximations.Statistics & Probability Letters, 211:110149, 2024.

Debiasing the Lasso under Weaker Tail Assumptions A remark on moment-dependent phase transitions in high- dimensional gaussian approximations.Statistics & Probability Letters, 211:110149, 2024

Reference 33

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Observation b7d1f692-244a-470c-ab88-0b07870d12de · outbound

This paper cites Springer Science & Business Media, 2011.

Debiasing the Lasso under Weaker Tail Assumptions Springer Science & Business Media, 2011

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.692818Z

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Observation a9527372-e82e-41b6-9337-3456c8e2fe27 · outbound

This paper cites Reconstruction from anisotropic random measurements.

Debiasing the Lasso under Weaker Tail Assumptions Reconstruction from anisotropic random measurements

Reference 35

Resolution: malformed identifier; no resolver link, observed 2026-08-15T14:47:18.697614Z

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Observation 69f4f8ce-b85c-491c-993a-f3b740013007 · outbound

This paper cites Restricted eigenvalue conditions on subgaussian random matrices.arXiv: Statistics Theory, 2009.

Debiasing the Lasso under Weaker Tail Assumptions Restricted eigenvalue conditions on subgaussian random matrices.arXiv: Statistics Theory, 2009

Reference 36

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Observation 7f54fe00-e9dc-4095-a296-e439ad748205 · outbound

This paper cites Sample average approximation with heavier tails II: localization in stochasticconvexoptimizationandpersistenceresultsforthelasso.Math.Program.,199(1-2):49–86,May2023.

Debiasing the Lasso under Weaker Tail Assumptions Sample average approximation with heavier tails II: localization in stochasticconvexoptimizationandpersistenceresultsforthelasso.Math.Program.,199(1-2):49–86,May2023

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:18.707089Z

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Pith citing papers

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