Paper Citation Record · LEDGER

Sparse minimum Redundancy Maximum Relevance for feature selection

As of 15 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2508.18901.

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

pith.paper-citation-record.v1
2508.18901 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:12:39.674155Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

49 of 49 outbound references displayed

verified exact0
verified fuzzy44
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9bd4e2c9-04f6-4522-b8fa-fc32c42e980a · outbound

This paper cites Ultrahigh dimensional feature screening via RKHS embeddings.

Sparse minimum Redundancy Maximum Relevance for feature selection Ultrahigh dimensional feature screening via RKHS embeddings

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.306388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0beb618e-26e9-4e00-8898-e7599f9b3652 · outbound

This paper cites Barber and Emmanuel J.

Sparse minimum Redundancy Maximum Relevance for feature selection Barber and Emmanuel J

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.294106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53c319c8-ad45-455a-b9e4-ac1883f4ea5c · outbound

This paper cites Barber and Emmanuel J.

Sparse minimum Redundancy Maximum Relevance for feature selection Barber and Emmanuel J

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.278131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8dbb3fd6-84d1-46a8-b00a-c6ebaa7dddd4 · outbound

This paper cites Cand \`e s, Yingying Fan, Lucas Janson, and Jinchi Lv.

Sparse minimum Redundancy Maximum Relevance for feature selection Cand \`e s, Yingying Fan, Lucas Janson, and Jinchi Lv

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.265490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53eb2660-f70d-4cc9-b3f7-0451cc612596 · outbound

This paper cites Cand \`e s, Yingying Fan, Lucas Janson, and Jinchi Lv.

Sparse minimum Redundancy Maximum Relevance for feature selection Cand \`e s, Yingying Fan, Lucas Janson, and Jinchi Lv

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.252209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 99d25705-db83-41c4-9bd6-b2f09f186d2b · outbound

This paper cites Block hsic lasso: model-free biomarker detection for ultra-high dimensional data.

Sparse minimum Redundancy Maximum Relevance for feature selection Block hsic lasso: model-free biomarker detection for ultra-high dimensional data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.239191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b68306c7-8d0c-43d1-a4f5-df0346734792 · outbound

This paper cites Global sensitivity analysis with dependence measures.

Sparse minimum Redundancy Maximum Relevance for feature selection Global sensitivity analysis with dependence measures

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.226559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0e734f59-e122-4250-aafd-a34fe4d2261a · outbound

This paper cites Bayesian Optimization for Machine Learning : A Practical Guidebook.

Sparse minimum Redundancy Maximum Relevance for feature selection Bayesian Optimization for Machine Learning : A Practical Guidebook

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T16:12:39.512421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 228e2eb4-671c-4d9d-bf1b-5edfcf5075d8 · outbound

This paper cites CVXPY : A P ython-embedded modeling language for convex optimization.

Sparse minimum Redundancy Maximum Relevance for feature selection CVXPY : A P ython-embedded modeling language for convex optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T16:12:39.516365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f1bd447-62f4-4070-9e46-9aef77ab9d22 · outbound

This paper cites Least angle regression.

Sparse minimum Redundancy Maximum Relevance for feature selection Least angle regression

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.206228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e5581c9-8fb3-4311-aa7e-ab59330010c1 · outbound

This paper cites Variable selection via nonconcave penalized likelihood and its oracle properties.

Sparse minimum Redundancy Maximum Relevance for feature selection Variable selection via nonconcave penalized likelihood and its oracle properties

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.194541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9d275ab1-54d7-46c8-a83c-8581a3f5acdb · outbound

This paper cites Sure independence screening for ultrahigh dimensional feature space.

Sparse minimum Redundancy Maximum Relevance for feature selection Sure independence screening for ultrahigh dimensional feature space

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.182409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c6451dd2-d6e5-4c1b-88fd-8a1059f17ba1 · outbound

This paper cites Nonconcave penalized likelihood with a diverging number of parameters.

Sparse minimum Redundancy Maximum Relevance for feature selection Nonconcave penalized likelihood with a diverging number of parameters

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.167633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bc2cba14-9ebd-4614-9a92-ab6972e0b83d · outbound

This paper cites Network exploration via the adaptive lasso and scad penalties.

Sparse minimum Redundancy Maximum Relevance for feature selection Network exploration via the adaptive lasso and scad penalties

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.155129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation da584171-24f0-48c7-9802-4779895fb4d8 · outbound

This paper cites Strong oracle optimality of folded concave penalized estimation.

Sparse minimum Redundancy Maximum Relevance for feature selection Strong oracle optimality of folded concave penalized estimation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.142269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 11edee67-cb4f-423c-8483-1cc0a8891507 · outbound

This paper cites Rank: Large-scale inference with graphical nonlinear knockoffs.

Sparse minimum Redundancy Maximum Relevance for feature selection Rank: Large-scale inference with graphical nonlinear knockoffs

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.130022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d0529a6c-faac-4555-9e64-171c47c97311 · outbound

This paper cites Fermanian and Benjamin Poignard.

Sparse minimum Redundancy Maximum Relevance for feature selection Fermanian and Benjamin Poignard

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.118014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c9b1b3b5-8991-4937-8e19-efc486cd0a63 · outbound

This paper cites Sriperumbudur.

Sparse minimum Redundancy Maximum Relevance for feature selection Sriperumbudur

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.105804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d6af030a-acbb-4e7d-8096-7b73614d83bc · outbound

This paper cites Type s error rates for classical and bayesian single and multiple comparison procedures.

Sparse minimum Redundancy Maximum Relevance for feature selection Type s error rates for classical and bayesian single and multiple comparison procedures

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.094122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf9e51e8-dce6-425b-b54e-302a60a283e2 · outbound

This paper cites Measuring statistical dependence with H ilbert- S chmidt norms.

Sparse minimum Redundancy Maximum Relevance for feature selection Measuring statistical dependence with H ilbert- S chmidt norms

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.082096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6d3c52db-af3f-4ad8-89c6-5150c141efe7 · outbound

This paper cites Kernel methods for measuring independence.

Sparse minimum Redundancy Maximum Relevance for feature selection Kernel methods for measuring independence

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.069699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 14c602a8-6a5e-47a7-8218-c1f451f8de12 · outbound

This paper cites Teo, Le Song, Bernhard Sch \"o lkopf, and Alex Smola.

Sparse minimum Redundancy Maximum Relevance for feature selection Teo, Le Song, Bernhard Sch \"o lkopf, and Alex Smola

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.057523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 23b1c06b-31de-4993-9735-c075bdb59474 · outbound

This paper cites Structure-based design and classifications of small molecules regulating the circadian rhythm period.

Sparse minimum Redundancy Maximum Relevance for feature selection Structure-based design and classifications of small molecules regulating the circadian rhythm period

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.045512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c5a2b379-5818-42aa-8c9c-30b329a3f76f · outbound

This paper cites An introduction to variable and feature selection.

Sparse minimum Redundancy Maximum Relevance for feature selection An introduction to variable and feature selection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.033339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 52c4885f-2678-4594-9a72-b1d86089c77a · outbound

This paper cites Sparsistency and rates of convergence in large covariance matrix estimation.

Sparse minimum Redundancy Maximum Relevance for feature selection Sparsistency and rates of convergence in large covariance matrix estimation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.020496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a46b653c-b0a0-4ea3-b4e4-bcc3d82982f6 · outbound

This paper cites Trevino, Jiliang Tang, and Huan Liu.

Sparse minimum Redundancy Maximum Relevance for feature selection Trevino, Jiliang Tang, and Huan Liu

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:40.008682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2b139dd5-2111-4593-85b2-564f16a42571 · outbound

This paper cites Feature screening via distance correlation learning.

Sparse minimum Redundancy Maximum Relevance for feature selection Feature screening via distance correlation learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.996729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 03f057df-3c99-4ab2-b89c-5ba9024ffe63 · outbound

This paper cites Model-free feature screening and fdr control with knockoff features.

Sparse minimum Redundancy Maximum Relevance for feature selection Model-free feature screening and fdr control with knockoff features

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.984201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 42e74b18-a679-4ae6-b5c9-75db1a86544c · outbound

This paper cites Loh and Martin J.

Sparse minimum Redundancy Maximum Relevance for feature selection Loh and Martin J

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.971704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8651490b-1c9f-4352-8ee2-3be4e4163743 · outbound

This paper cites an unresolved cited work.

Sparse minimum Redundancy Maximum Relevance for feature selection Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:12:39.958197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c0af18df-3507-422d-8ebe-5cd78323610b · outbound

This paper cites The kolmogorov filter for variable screening in high dimensional binary classification.

Sparse minimum Redundancy Maximum Relevance for feature selection The kolmogorov filter for variable screening in high dimensional binary classification

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.946293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eec11150-d6de-4902-a51c-e9a64080d997 · outbound

This paper cites The fused kolmogorov filter: A nonparametric model-free screening method.

Sparse minimum Redundancy Maximum Relevance for feature selection The fused kolmogorov filter: A nonparametric model-free screening method

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.934239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c3cec37a-fe47-46ba-83f9-37d98df8d1e8 · outbound

This paper cites Prediction of treatment response in triple negative breast cancer from whole slide images.

Sparse minimum Redundancy Maximum Relevance for feature selection Prediction of treatment response in triple negative breast cancer from whole slide images

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.922145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b357fc76-6b8b-4e70-9c52-bd9ea2de6706 · outbound

This paper cites Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy.

Sparse minimum Redundancy Maximum Relevance for feature selection Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.910179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 82fa7a83-1284-4a80-8283-d718717cf1b5 · outbound

This paper cites Fermanian.

Sparse minimum Redundancy Maximum Relevance for feature selection Fermanian

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.898007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fe8fea47-b76e-4467-a574-ff5f48df69d1 · outbound

This paper cites Sparse hilbert-schmidt independence criterion regression.

Sparse minimum Redundancy Maximum Relevance for feature selection Sparse hilbert-schmidt independence criterion regression

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.885238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5f31dfbb-c267-4cfd-8fbb-3460e4c3dbd6 · outbound

This paper cites Feature screening with kernel knockoffs.

Sparse minimum Redundancy Maximum Relevance for feature selection Feature screening with kernel knockoffs

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.873161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 76323ccb-4424-4e35-b5b4-010ff2638f0f · outbound

This paper cites Cand\`es.

Sparse minimum Redundancy Maximum Relevance for feature selection Cand\`es

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.860538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0ab59143-8056-43c5-9c06-db94425b5cea · outbound

This paper cites Serfling.

Sparse minimum Redundancy Maximum Relevance for feature selection Serfling

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.848170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9187b6e2-0cf4-4185-89c2-5bab9356f4c4 · outbound

This paper cites Feature selection via dependence maximization.

Sparse minimum Redundancy Maximum Relevance for feature selection Feature selection via dependence maximization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.836380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 18bb14f4-edb8-47ce-a276-1714f10cc3c3 · outbound

This paper cites Compositional knockoff filter for high-dimensional regression analysis of microbiome data.

Sparse minimum Redundancy Maximum Relevance for feature selection Compositional knockoff filter for high-dimensional regression analysis of microbiome data

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.824571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 80df7c30-cf7b-48af-bca3-9df5a37486bd · outbound

This paper cites Sz \'e kely and Maria L.

Sparse minimum Redundancy Maximum Relevance for feature selection Sz \'e kely and Maria L

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.812671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4c9b45d4-d3f1-4008-87d9-6a3b53b554b7 · outbound

This paper cites Sz \'e kely, Maria L.

Sparse minimum Redundancy Maximum Relevance for feature selection Sz \'e kely, Maria L

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.801166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a96d3411-5fa0-486f-a209-9b18ffeb7252 · outbound

This paper cites an unresolved cited work.

Sparse minimum Redundancy Maximum Relevance for feature selection Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:12:39.788115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e74eb2b3-bd5f-49a2-bbee-8ec1c5e4a137 · outbound

This paper cites Regression shrinkage and selection via the lasso.

Sparse minimum Redundancy Maximum Relevance for feature selection Regression shrinkage and selection via the lasso

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.774618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c694b7ce-fc2d-40f5-8415-764117fbdda6 · outbound

This paper cites Xing, and Masashi Sugiyama.

Sparse minimum Redundancy Maximum Relevance for feature selection Xing, and Masashi Sugiyama

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.759817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 81a87e0f-bc86-43e4-8269-38b760a50be6 · outbound

This paper cites an unresolved cited work.

Sparse minimum Redundancy Maximum Relevance for feature selection Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-05T16:12:39.745725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4f298dbf-e9ab-4fcf-9322-a6e171e3d86d · outbound

This paper cites Projection correlation between two random vectors.

Sparse minimum Redundancy Maximum Relevance for feature selection Projection correlation between two random vectors

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.732182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e23fc5ab-21cc-419b-b2cb-239ad28e90ed · outbound

This paper cites One-step sparse estimates in nonconcave penalized likelihood models.

Sparse minimum Redundancy Maximum Relevance for feature selection One-step sparse estimates in nonconcave penalized likelihood models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T16:12:39.719182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.