Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-14T05:58:32.336515Z
Paper Citation Record · LEDGER
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis
As of 11 August 2026, this Paper Citation Record lists 100 of 232 outbound references and 0 inbound Pith citation observations for arXiv:2607.11256.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
100 of 232 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved100
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 66e62ef0-5907-464c-ae44-f7d5ebdd92b2 · outbound
This paper cites Electronic Journal of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Electronic Journal of Statistics , volume=
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8fbc46a-0e21-43cf-ab16-eb844f4bbcfb · outbound
This paper cites Nature genetics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Nature genetics , volume=
Reference 2
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Observation e67d2779-d198-4ca9-af7e-eb075a6f6fc7 · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume =.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume =
Reference 3
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Observation ada821f2-e707-4c60-8d53-465cb5894967 · outbound
This paper cites Jackknife multiplier bootstrap: finite sample approximations to the.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Jackknife multiplier bootstrap: finite sample approximations to the
Reference 4
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e60d11e-dcdb-42d7-97d9-cbdc4c0dca50 · outbound
This paper cites Journal of Multivariate Analysis , volume =.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Multivariate Analysis , volume =
Reference 5
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- unresolved
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Source-reported events for the cited work
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Observation 4ec23f30-5258-4810-8808-a36397396f4f · outbound
This paper cites and Owens, D.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis and Owens, D
Reference 6
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7bc0737-b1f2-4374-a67f-30740ab9f938 · outbound
This paper cites and Zhu, H.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis and Zhu, H
Reference 7
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 5787e07f-32b8-4c8d-87c9-eda3ded2c4a4 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 8
- Resolution
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Observation 61ff5a4f-1003-4777-8f04-5b31435f06f8 · outbound
This paper cites Test , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Test , volume=
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 291424d5-6fe4-4ff0-b080-a285580fe889 · outbound
This paper cites Statistica Sinica , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistica Sinica , pages=
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Unavailable: canonical work link unavailable.
Observation a3c1582d-e726-4420-800e-6eb3b56f8e09 · outbound
This paper cites High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity
Reference 12
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Observation 854874fe-9619-4742-9e78-598d72bf2efb · outbound
This paper cites 2021 , journal =.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis 2021 , journal =
Reference 13
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Observation c29cc2b4-1fe4-4dd1-ae19-ae8deca3fd50 · outbound
This paper cites arXiv preprint arXiv:2308.04368 , year=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis arXiv preprint arXiv:2308.04368 , year=
Reference 14
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0db73b99-cd30-482b-9b46-3246831eb9e1 · outbound
This paper cites Statistica Sinica , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistica Sinica , pages=
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Unavailable: canonical work link unavailable.
Observation b24e15af-5355-4a56-a1d4-fe54d1fd7bb0 · outbound
This paper cites 2021 , journal=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis 2021 , journal=
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
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Observation 4c337eb0-688d-427a-8923-cec37af37da9 · outbound
This paper cites Change point inference in high-dimensional regression models under temporal dependence.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Change point inference in high-dimensional regression models under temporal dependence
Reference 17
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8db09a07-30b7-41b4-ad91-b6f2e20a10b3 · outbound
This paper cites International Conference on Artificial Intelligence and Statistics , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis International Conference on Artificial Intelligence and Statistics , pages=
Reference 18
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 52e43089-54fc-4d54-8c7b-97731d574bb9 · outbound
This paper cites Journal of Royal Statistical Society, Series B , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Royal Statistical Society, Series B , volume=
Reference 19
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 907f5c74-1f8f-4752-97cd-dd27408412ed · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 20
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 452d3e05-935d-4d3e-a86b-afdf82410dd1 · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 21
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Unavailable: canonical work link unavailable.
Observation b0ff7e0c-5c1b-428e-a06d-5bc63f0a95ec · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 22
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56bf094b-54fa-4b4f-bdaf-9c95c4b3dc18 · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 23
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Unavailable: canonical work link unavailable.
Observation bd08c1cc-2424-448b-bb37-3eb0ab29aad0 · outbound
This paper cites an unresolved cited work.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Unresolved cited work
Reference 24
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- unresolved
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Observation c959895b-9ae1-4dc8-aef2-97ad5a6439d9 · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Unavailable: canonical work link unavailable.
Observation 30153c61-60ff-4fea-80b1-9600fb305508 · outbound
This paper cites Journal of.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of
Reference 26
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16be6631-6c1d-48fd-8df0-1d6cfe5cdb76 · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 27
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7433515f-bd40-4784-a512-d94014ae4db4 · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 28
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca40bef6-eac0-455c-8f18-03faf5157622 · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da6e23c7-ea50-4b72-ab70-12f9cbbd8271 · outbound
This paper cites A Unified Framework for Testing High Dimensional Parameters: A Data-Adaptive Approach.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis A Unified Framework for Testing High Dimensional Parameters: A Data-Adaptive Approach
Reference 30
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9003d161-e2b4-4733-862b-3b24390789f2 · outbound
This paper cites On the Maximal Perimeter of a Convex Set in.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis On the Maximal Perimeter of a Convex Set in
Reference 31
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fabc464-0977-498c-ad3e-4e02f40a4d1f · outbound
This paper cites Electronic Journal of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Electronic Journal of Statistics , volume=
Reference 32
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a5c6807-a96b-49bd-a284-90d46bc67ace · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 33
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9de5844-311c-456b-a700-46c3b3ca8824 · outbound
This paper cites Concentration.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Concentration
Reference 34
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c227af38-dbf0-4fe6-9934-79dd384ef433 · outbound
This paper cites Submitted , year=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Submitted , year=
Reference 35
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a872ebd-640e-47ec-bf47-0bd82150d4e3 · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 36
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e8a384c-f3c9-4e50-a194-d1e9f811c27d · outbound
This paper cites Journal of Royal Statistical Society, Series B (Statistical Methodology) , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Royal Statistical Society, Series B (Statistical Methodology) , pages=
Reference 37
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 222257cb-918a-4dba-bb96-943312027d03 · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 38
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 120d6d93-ac4b-4737-a333-396112ae106a · outbound
This paper cites Statistica Sinica , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistica Sinica , volume=
Reference 39
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73624a07-d753-4725-acad-d974197df05d · outbound
This paper cites The Annals of Probability , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Probability , volume=
Reference 40
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Unavailable: canonical work link unavailable.
Observation 18c3a4a5-b3ee-4fcd-94b3-7027cfba1486 · outbound
This paper cites Gaussian and bootstrap approximations for high-dimensional.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Gaussian and bootstrap approximations for high-dimensional
Reference 41
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9ee1398-b3c8-4fe8-9b8b-6cb21e91fc7a · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 42
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3dc393d2-160c-4d52-a3e7-56acc545abbe · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 43
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3ca4c16-4f69-42a9-83d3-29aa21e1457d · outbound
This paper cites Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Annals of Statistics , volume=
Reference 44
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10c3e938-a852-448c-b9d8-c024a9b04436 · outbound
This paper cites The Journal of Machine Learning Research , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Journal of Machine Learning Research , volume=
Reference 45
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- unresolved
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Unavailable: canonical work link unavailable.
Observation 60550007-074e-4346-a621-fd13be87da32 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 46
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 69ce9d77-f811-41b7-8b24-b06acb292277 · outbound
This paper cites The Journal of Machine Learning Research , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Journal of Machine Learning Research , volume=
Reference 47
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0549905a-79f8-4f24-8246-6923875bccdf · outbound
This paper cites 2011 , publisher=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis 2011 , publisher=
Reference 48
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5affb57f-7007-407a-a973-919e848f736d · outbound
This paper cites Biometrika , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Biometrika , volume=
Reference 49
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf1de3c6-9089-4493-bc83-0f8168d48f54 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e1e4d1a-4910-430d-963a-9a7aa0e0d559 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 51
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a64198ec-3370-43bd-9cf2-356037620236 · outbound
This paper cites Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistics , volume=
Reference 52
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 062412e1-3188-410e-9be2-789a8874a4a3 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 53
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36476dc9-77c9-499f-8df1-cd1f894acaef · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 54
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2359d0f3-4679-47aa-9fa3-40206eebd9c2 · outbound
This paper cites Journal of Multivariate Analysis , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Multivariate Analysis , volume=
Reference 55
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf90f097-3aba-470c-b9f6-f8301133276b · outbound
This paper cites Econometrica , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Econometrica , volume=
Reference 56
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e4c182c-754e-4279-8be2-3eadc9a2656d · outbound
This paper cites 1997 , publisher=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis 1997 , publisher=
Reference 57
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4be20f06-7bda-4e7d-bc5e-d82cf968b441 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 58
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- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2fb889e-7984-427e-8663-46718687bd0e · outbound
This paper cites In: 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton) , publisher=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis In: 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton) , publisher=
Reference 60
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ffc993a9-f19d-41a5-82ef-ef8149e1ba4c · outbound
This paper cites Journal of Royal Statistical Society, Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Royal Statistical Society, Series B (Statistical Methodology) , volume=
Reference 61
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- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a370a21-a378-41d7-83eb-9155c74227dd · outbound
This paper cites Soviet Math.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Soviet Math
Reference 62
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Observation b4882196-d71d-49f9-91d4-b7b087f555c6 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 63
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Observation ebee3879-08fc-4245-91fc-de1493ef136b · outbound
This paper cites Quarterly Journal of Economics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Quarterly Journal of Economics , volume=
Reference 64
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Observation 8e3caa79-7804-488d-a7f7-9253897a0f43 · outbound
This paper cites Journal of Economic Dynamics and Control , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Economic Dynamics and Control , volume=
Reference 65
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Observation fa1a3118-e0ce-4839-9111-a819c917620e · outbound
This paper cites Statistics and Computing , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistics and Computing , volume=
Reference 66
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Observation d5ce94ac-c958-42da-92d8-d287ab380e18 · outbound
This paper cites Technometrics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Technometrics , volume=
Reference 67
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Observation fff874c0-3eea-417b-91f6-a702c24d5719 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 68
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Observation d78d1c50-ced9-49e3-9d2e-09dfed796024 · outbound
This paper cites Statistics and Computing , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistics and Computing , volume=
Reference 69
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- unresolved
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Observation 80a5182a-fc16-485a-8208-230d0a3f7090 · outbound
This paper cites Journal of the American Statistical Association , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , volume=
Reference 70
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Observation e459977d-ced8-413d-8923-74a940c0b398 · outbound
This paper cites Bernoulli , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Bernoulli , volume=
Reference 71
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Observation 2810231d-8d97-4b7a-84ad-3901d145ede1 · outbound
This paper cites Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Annals of Statistics , volume=
Reference 72
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 6c34c6d9-7c5d-4725-a0e0-50cc13bddaa5 · outbound
This paper cites Statistica Sinica , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Statistica Sinica , volume=
Reference 73
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Observation 055c7da6-d294-4c22-b478-fc5d82b8b2d5 · outbound
This paper cites and Folstein, Susan E.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis and Folstein, Susan E
Reference 74
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Observation 967f150c-5dd0-4d10-8f53-0458a7d407a7 · outbound
This paper cites Journal of the American Statistical Association , year=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association , year=
Reference 75
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Observation c53338c0-6ae4-4c8d-bd9f-bbaa92a0ffb5 · outbound
This paper cites Multi-Modal Multi-Task Learning for Joint Prediction of Multiple Regression and Classification Variables in.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Multi-Modal Multi-Task Learning for Joint Prediction of Multiple Regression and Classification Variables in
Reference 76
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Observation 4fbdbe19-9946-4bd5-a127-c0f0a5b9c93d · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 77
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Observation 2745f268-f7cc-4a8f-8ad9-1e6b888a7156 · outbound
This paper cites Structural Break Detection in High-Dimensional Non-Stationary.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Structural Break Detection in High-Dimensional Non-Stationary
Reference 78
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Observation 1fc6e894-b9ee-475a-a4cb-45261827e8a3 · outbound
This paper cites Biometrics , year=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Biometrics , year=
Reference 79
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Observation eddc6cc4-d2af-4fd3-acf5-00b17c753f15 · outbound
This paper cites Lin and Rebecca Willett , title =.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Lin and Rebecca Willett , title =
Reference 80
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Observation 82494e2b-d90f-402d-94d1-e412861c8c95 · outbound
This paper cites Restricted eigenvalue properties for correlated.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Restricted eigenvalue properties for correlated
Reference 81
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Observation e2afb8a9-d81f-4dcc-8633-06864cd41153 · outbound
This paper cites Electronic Journal of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Electronic Journal of Statistics , volume=
Reference 82
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Observation 8154d5a4-c25f-41ea-9bd1-0257f2954ed7 · outbound
This paper cites , author=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis , author=
Reference 83
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Observation 59707852-8214-4aed-8030-7c3f07c9363f · outbound
This paper cites Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society: Series B (Statistical Methodology) , volume=
Reference 84
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Observation 6ebe8272-3884-49a0-9604-d55f5744e678 · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 85
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Observation b98a10ce-bdd9-4aae-b6a8-ccf2827d5600 · outbound
This paper cites International Conference on Artificial Intelligence and Statistics , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis International Conference on Artificial Intelligence and Statistics , pages=
Reference 86
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Observation f24c4b4f-9f75-447a-80fb-0938d3638a9d · outbound
This paper cites Journal of Econometrics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Econometrics , volume=
Reference 87
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Observation fe0b1f00-dd03-42a3-8766-1b2a8b6b370e · outbound
This paper cites Common change point estimation in panel data from the least squares and maximum likelihood viewpoints.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Common change point estimation in panel data from the least squares and maximum likelihood viewpoints
Reference 88
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Observation ba66c5f5-6c9c-40ab-b2aa-67f5a9157af3 · outbound
This paper cites Journal of the American Statistical Association, to appear , year=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association, to appear , year=
Reference 90
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Observation 614bbb78-bbdc-4ab7-9ba4-84420cac7d30 · outbound
This paper cites Dating the Break in High-dimensional Data.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Dating the Break in High-dimensional Data
Reference 91
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Observation 3ef81535-eaf1-4999-b59e-5280923e119f · outbound
This paper cites Electronic Journal of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Electronic Journal of Statistics , volume=
Reference 92
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- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 457423a9-6688-4203-9a2c-dc823969a39b · outbound
This paper cites Review of Economics and Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Review of Economics and Statistics , volume=
Reference 93
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- unresolved
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Observation b3b4489a-2e3b-4f47-bfea-d3978ae9852b · outbound
This paper cites Change-point detection in panel data via double.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Change-point detection in panel data via double
Reference 94
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Observation 779afb9a-064c-4636-a859-00d7176abaf8 · outbound
This paper cites Inference for Change Points in High Dimensional Data via Self-Normalization.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Inference for Change Points in High Dimensional Data via Self-Normalization
Reference 95
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Observation 28c58e4f-1d9e-4b50-87ae-0f95904ae27e · outbound
This paper cites The Annals of Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis The Annals of Statistics , volume=
Reference 96
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T05:58:32.336515Z
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Observation 7d16c501-f9ec-4117-9ca7-5d0edde5f178 · outbound
This paper cites Journal of the American Statistical Association,to appear , pages=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the American Statistical Association,to appear , pages=
Reference 97
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- unresolved
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Observation e99250e6-9db4-4ffb-96bf-25b650a68a52 · outbound
This paper cites Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Disentangling sex-dependent effects of APOE on diverse trajectories of cognitive decline in
Reference 98
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Observation e66ead41-1c3c-4602-83d3-d643a20d194a · outbound
This paper cites Annals of Applied Statistics , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Annals of Applied Statistics , volume=
Reference 99
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Observation a0a167cc-80c1-42cb-ab3b-a07338feca72 · outbound
This paper cites 2002 , publisher =.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis 2002 , publisher =
Reference 100
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Observation afbbe8e6-d14b-4c2f-bade-17bcca2a9377 · outbound
This paper cites Journal of Multivariate Analysis , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of Multivariate Analysis , volume=
Reference 101
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Observation 933d8475-d26c-4958-8dd5-bb71d9a36a55 · outbound
This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=
Reference 102
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Observation f8a44d5f-4b5c-43b9-b5c0-e4767adfe6bb · outbound
This paper cites Inference for.
A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis Inference for
Reference 103
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Pith citing papers
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