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Paper Citation Record · LEDGER

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming

As of 23 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2608.12757.

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

pith.paper-citation-record.v1
2608.12757 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:58:52.497022Z

measured 54 of 54 standing notices

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measured 0 of 0 inbound itemization

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

54 of 54 outbound references displayed

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External citation measurements

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Outbound references

Observation ea2f7b92-d9d4-4e87-9dd0-f09e68b9aef1 · outbound

This paper cites Distributed majorization-minimization for Laplacian regularized problems,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Distributed majorization-minimization for Laplacian regularized problems,

Reference 1

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Observation 2aa6dc77-4d30-453c-af54-b1960233e3b5 · outbound

This paper cites Laplacian regularized low-rank represen- tation and its applications,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Laplacian regularized low-rank represen- tation and its applications,

Reference 2

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Observation ff02d519-5cbb-4e26-84c1-cdde8549aee3 · outbound

This paper cites Semi-supervised ranking on very large graphs with rich metadata,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Semi-supervised ranking on very large graphs with rich metadata,

Reference 3

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This paper cites Representing docu- ments through their readers,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Representing docu- ments through their readers,

Reference 4

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Observation 38410fb0-176b-4128-b53e-3aed69310898 · outbound

This paper cites A graph Laplacian regular- ization for hyperspectral data unmixing,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming A graph Laplacian regular- ization for hyperspectral data unmixing,

Reference 5

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Observation ceff8516-79fd-4f4f-aa8c-8e6912dd5edb · outbound

This paper cites Graph regularized nonnegative matrix factorization for data representation,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Graph regularized nonnegative matrix factorization for data representation,

Reference 6

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Observation ba99fc32-4b2e-4436-ae65-acf0eb3f3d91 · outbound

This paper cites Laplacian regularized nonnegative representation for clustering and dimensionality reduction,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Laplacian regularized nonnegative representation for clustering and dimensionality reduction,

Reference 7

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Observation dcc8b562-41aa-4445-9e3d-102c731a199a · outbound

This paper cites Boyd and L.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Boyd and L

Reference 8

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Observation 2d324787-621b-4af5-b2f4-b590835b04a3 · outbound

This paper cites Incremental computation of pseudoinverse of Laplacian,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Incremental computation of pseudoinverse of Laplacian,

Reference 9

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Observation 191f6881-45ad-427d-b28e-54ae58d95aad · outbound

This paper cites Maintainability and scal- ability in machine learning: Challenges and solutions,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Maintainability and scal- ability in machine learning: Challenges and solutions,

Reference 10

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Observation 4367e388-4c7f-4053-8c99-7eed513ae823 · outbound

This paper cites Wavelets on graphs via spectral graph theory,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Wavelets on graphs via spectral graph theory,

Reference 11

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Observation 5213af12-955d-4b0d-8985-cdb0ba8e2f32 · outbound

This paper cites Dis- tributed signal processing via Chebyshev polynomial approximation,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Dis- tributed signal processing via Chebyshev polynomial approximation,

Reference 12

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Observation c44f03cc-17eb-4d0d-a0ff-0097150da05f · outbound

This paper cites Iterative polynomial approximation algorithms for inverse graph filters,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Iterative polynomial approximation algorithms for inverse graph filters,

Reference 13

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Observation a8349594-efbc-411b-b3fd-8a6a06737981 · outbound

This paper cites Graph convolutions enrich the self-attention in transformers!.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Graph convolutions enrich the self-attention in transformers!

Reference 14

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Observation 2310c029-7ed0-428f-8493-e280b2b110a0 · outbound

This paper cites Learning spectral graph transforma- tions for link prediction,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Learning spectral graph transforma- tions for link prediction,

Reference 15

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Observation c5039071-b6da-4af0-9d97-318cbc8c0622 · outbound

This paper cites Learning the kernel via convex optimization,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Learning the kernel via convex optimization,

Reference 16

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Observation 39670cbf-ee30-45bd-9597-7402daafd483 · outbound

This paper cites Graph learning,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Graph learning,

Reference 17

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Observation 777dd9af-8ec1-4f75-b30e-3cbf9cab18d8 · outbound

This paper cites Duality in DC (difference of convex functions) optimization. Subgradient methods,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Duality in DC (difference of convex functions) optimization. Subgradient methods,

Reference 18

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Observation 14bf5f03-239e-4cab-9980-ce62a719304f · outbound

This paper cites Disciplined convex-concave programming,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Disciplined convex-concave programming,

Reference 19

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Source-reported events for the cited work

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Observation fe2a435a-126f-46a6-9aa5-54afd3304429 · outbound

This paper cites A globally convergent difference-of-convex algorithmic framework and application to log-determinant optimization problems.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming A globally convergent difference-of-convex algorithmic framework and application to log-determinant optimization problems

Reference 20

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Observation b5c768e0-bdd3-4156-a6d3-2c6100e9ead9 · outbound

This paper cites Minimizing oracle-structured composite functions,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Minimizing oracle-structured composite functions,

Reference 21

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Observation 2b4a2364-9eed-4f8c-897d-1f76d2b0b773 · outbound

This paper cites Computing one-bit compressive sensing via zero-norm regularized DC loss model and its surrogate,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Computing one-bit compressive sensing via zero-norm regularized DC loss model and its surrogate,

Reference 22

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Observation 4a45bee4-bf6c-4844-9857-3a7e5a687a6a · outbound

This paper cites Direct-optimization-based DC dictionary learning with the MCP regularizer,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Direct-optimization-based DC dictionary learning with the MCP regularizer,

Reference 23

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Observation 169e6962-b63c-41ab-a9bb-378269f4e105 · outbound

This paper cites A DC optimization algorithm for solving the trust-region subproblem,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming A DC optimization algorithm for solving the trust-region subproblem,

Reference 24

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Observation 2b680b2a-39c5-40c5-98e7-d275a33167ef · outbound

This paper cites Duality in nonconvex optimization,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Duality in nonconvex optimization,

Reference 25

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Observation a16e5309-f076-4d9c-9bf7-7ba1d19ec061 · outbound

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Difference-of-Convex Regularization for Graph Learning by Differentiable Programming The concave-convex procedure,

Reference 26

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Source-reported events for the cited work

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This paper cites Variations and extension of the convex–concave procedure,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Variations and extension of the convex–concave procedure,

Reference 27

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Difference-of-Convex Regularization for Graph Learning by Differentiable Programming The concave-convex procedure (CCCP),

Reference 28

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Observation 0c076383-e052-42bf-817e-548a58e25ae0 · outbound

This paper cites Accelerating Regularized Attention Kernel Regression for Spectrum Cartography.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Accelerating Regularized Attention Kernel Regression for Spectrum Cartography

Reference 29

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Observation 275cc612-8b24-4a4e-965e-6b5316a3a111 · outbound

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Difference-of-Convex Regularization for Graph Learning by Differentiable Programming The Elements of Differentiable Programming

Reference 30

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Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Learning to Optimize by Differentiable Programming

Reference 31

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Observation f10dc339-ce0e-4fa9-b06f-c83b57754daf · outbound

This paper cites A multivariate regression approach to association analysis of a quantitative trait network,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming A multivariate regression approach to association analysis of a quantitative trait network,

Reference 32

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Observation 81bdc2bc-e399-4412-8a1b-a905572d677c · outbound

This paper cites Smoothing proximal gradient method for general structured sparse regression,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Smoothing proximal gradient method for general structured sparse regression,

Reference 33

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Observation e1a079ce-83e7-4ec1-bd87-25d6441b0b2f · outbound

This paper cites Generalized Laplacian precision matrix estima- tion for graph signal processing,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Generalized Laplacian precision matrix estima- tion for graph signal processing,

Reference 34

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Source-reported events for the cited work

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Observation 4bc5c169-778c-42e8-9d0a-2fbe459e19f4 · outbound

This paper cites Non-negative low rank and sparse graph for semi-supervised learning,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Non-negative low rank and sparse graph for semi-supervised learning,

Reference 35

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Observation 47ed2e87-4be2-4e0d-ad32-c7eaa6feb694 · outbound

This paper cites Forging the graphs: A low rank and positive semidefinite graph learning approach,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Forging the graphs: A low rank and positive semidefinite graph learning approach,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.899753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 59320890-027e-48e6-88bc-de800e568cdc · outbound

This paper cites Pseudoinverse graph convolutional networks,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Pseudoinverse graph convolutional networks,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.889424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.440974Z digest=sha256:de747150ac481626d5e6a7b0048f5a9396dc11127b081ce25adb6906c8c05dbf

Observation 41c21cc1-8f03-4724-b195-e4b75824a7ed · outbound

This paper cites An efficient implementation to compute the pseudoinverse for the incremental broad learning system on added inputs,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming An efficient implementation to compute the pseudoinverse for the incremental broad learning system on added inputs,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.878366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 331bc17b-9aed-424f-b255-969275ab8f0b · outbound

This paper cites Diagonal of pseudoinverse of graph Laplacian: Fast estimation and exact results,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Diagonal of pseudoinverse of graph Laplacian: Fast estimation and exact results,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.868022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.447744Z digest=sha256:43f16927d311db37b57ad648c659cceabc1729cab757be3ef5f0716f4801a523

Observation 97171ebb-bb6e-4d8d-87be-d3d270d8e727 · outbound

This paper cites Strang,Introduction to Linear Algebra.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Strang,Introduction to Linear Algebra

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.857567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.450656Z digest=sha256:bdaa765dc679a1e3307fa9dd5f457c16a40b7d883d55aa9e26d4588d0155244f

Observation a5d97888-79db-4b64-bfef-1d667340776c · outbound

This paper cites CVXPY: A Python-embedded modeling lan- guage for convex optimization,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming CVXPY: A Python-embedded modeling lan- guage for convex optimization,

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.453998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.453998Z digest=sha256:e95f33411f5e92db91d7df2271a86b83771c0a4a74125545f85062635800b99e

Observation fda17bb1-28d0-478e-a7b0-e51308e8932a · outbound

This paper cites A distribution-free M-estimator of multivariate scatter,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming A distribution-free M-estimator of multivariate scatter,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.840252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.457032Z digest=sha256:4870f8d883efd50d74b83972bf56188fb335b1c5782e97cb556c6e669d814902

Observation bfcd8a65-4b0e-4c35-ac7a-b160c29b64d6 · outbound

This paper cites Regularized Tyler’s scatter estimator: Existence, uniqueness, and algorithms,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Regularized Tyler’s scatter estimator: Existence, uniqueness, and algorithms,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.460689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.460689Z digest=sha256:60296aa73e16d1b013320e77f278a4001f423c371108b66063e727eb11b1b15e

Observation 47691297-91bf-4ee2-ada4-77bcfb1b85a8 · outbound

This paper cites Tyler’s estimator performance analysis,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Tyler’s estimator performance analysis,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.463872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.463872Z digest=sha256:d6671c106b6f2e4ad9a779c54ae0c3e01867c00f4b893181c6c897f853c71210

Observation be4549f7-af53-44b0-bcdd-6b413287e94e · outbound

This paper cites an unresolved cited work.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-15T23:58:52.818147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.467052Z digest=sha256:763ccb3d7bff315cdf6b5481f52a3bd4af20316a1faddfdb6fca86d00ceb9375

Observation 09b59966-56e4-45ed-9d4b-bb5fdc8c2c93 · outbound

This paper cites On the mathematical foundations of theoretical statistics,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming On the mathematical foundations of theoretical statistics,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.807408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.470269Z digest=sha256:2377769103fb21788c34206380b099eb43cd0814123ea4bc7c0a4d8e5cda14a8

Observation d74b04f8-9c43-40e3-a407-7a7bc7aba75f · outbound

This paper cites An algorithm for quadratic programming,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming An algorithm for quadratic programming,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.473784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.473784Z digest=sha256:076455dedc0355103622d40ea5699754f68c7b487fc31f28dd5047ba930348e1

Observation 645dc3ce-00da-454b-be5e-f98f2c4bb3f4 · outbound

This paper cites Frank-Wolfe algorithm for DC optimization problem,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Frank-Wolfe algorithm for DC optimization problem,

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.477265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.477265Z digest=sha256:5d86e9407fa33da1c9b9d561797374d36b326020b85a230e711f43b8e1d7a578

Observation 1f7895d5-64ae-4b9e-a0ca-9a2150d8c3c7 · outbound

This paper cites CCCP is Frank-Wolfe in disguise,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming CCCP is Frank-Wolfe in disguise,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.791559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.480331Z digest=sha256:e314baa3ac8a6696bf9a87318aa82bd988fd8108c16a12c061fab519cac1161d

Observation 927bf709-fef2-4f2d-ba47-163a89f06233 · outbound

This paper cites Wireless network optimization by Perron-Frobenius theory,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Wireless network optimization by Perron-Frobenius theory,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.781625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.483583Z digest=sha256:d08d59e48dd34e8da67a989954fd9c17aa5490c5e171506bdeb1017fe937c92f

Observation 5a37d476-9970-4a4c-916a-a925373d4eaf · outbound

This paper cites Lemmens and R.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Lemmens and R

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.770468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.486590Z digest=sha256:e035e02a31241ed3e10d2632d560f37723c0d3b595294e491ccc2d02b48a3a81

Observation 825ade49-4ccb-407a-abe6-f4aac4bb38d9 · outbound

This paper cites Unified framework to regularized covariance estimation in scaled Gaussian models,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Unified framework to regularized covariance estimation in scaled Gaussian models,

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.489577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.489577Z digest=sha256:17314754e10493670f03635716f7cad5c062a1756113dd0fecffd7df7f89d4e5

Observation 91f845db-edcf-44c7-9f0d-9448781ceec3 · outbound

This paper cites Robust shrinkage estimation of high-dimensional covariance matrices,.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Robust shrinkage estimation of high-dimensional covariance matrices,

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T23:58:52.493693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:58:52.493693Z digest=sha256:5979b0da7eac7ffa2d87c7169baddb133819b67a75ef326b768ab95e67114884

Observation 11dbd301-bb9e-49df-ae46-698541e027d2 · outbound

This paper cites Granas, J.

Difference-of-Convex Regularization for Graph Learning by Differentiable Programming Granas, J

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:58:52.630365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-15T23:58:52.497022Z digest=sha256:1cd9b0a7a889c01a9351aafb77ee165eeec11c784d4a90a74f75d3bd9c187747

Pith citing papers

No inbound Pith citation observations are available.