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Paper Citation Record · LEDGER

Improved large-scale graph learning through ridge spectral sparsification

As of 23 July 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2604.20078.

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

pith.paper-citation-record.v1
2604.20078 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T00:25:51.723028Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-22T06:31:00.163083+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

35 of 35 outbound references displayed

  • verified exact18
  • verified fuzzy16
  • unresolved0
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f9e37ab5-0f4f-49f4-baf3-88c926c0500f · outbound

This paper cites Graph based anomaly detection and description: a survey.Data Mining and Knowledge Discovery, 29(3):626–688.

Improved large-scale graph learning through ridge spectral sparsification Graph based anomaly detection and description: a survey.Data Mining and Knowledge Discovery, 29(3):626–688

Reference 1

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Observation c9726d66-52cc-4276-bfd2-c53da05cd39c · outbound

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Improved large-scale graph learning through ridge spectral sparsification Unresolved cited work

Reference 2

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Observation acbde9f2-5dde-4469-b13b-805d58eb7c15 · outbound

This paper cites and Niyogi, P.

Improved large-scale graph learning through ridge spectral sparsification and Niyogi, P

Reference 3

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This paper cites http://people.cs.uchicago.edu/ niyogi/papersps/reg_colt.pdf Regularization and Semi-Supervised Learning on Large Graphs.

Improved large-scale graph learning through ridge spectral sparsification http://people.cs.uchicago.edu/ niyogi/papersps/reg_colt.pdf Regularization and Semi-Supervised Learning on Large Graphs

Reference 4

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Observation 3c46c2ac-09bc-4c56-8734-4c04223c876e · outbound

This paper cites On manifold regularization.

Improved large-scale graph learning through ridge spectral sparsification On manifold regularization

Reference 5

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Observation a92625f9-21dd-4678-a428-965fbffc8ebe · outbound

This paper cites and Van De Geer, S.

Improved large-scale graph learning through ridge spectral sparsification and Van De Geer, S

Reference 6

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Observation 8b6a9c00-2d26-4316-ad63-9030446dbc46 · outbound

This paper cites Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting.

Improved large-scale graph learning through ridge spectral sparsification Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting

Reference 7

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Observation 1c710685-0d4f-48d1-8cb9-ed6437b71c64 · outbound

This paper cites Distributed sequential sampling for kernel matrix approximation http://proceedings.mlr.press/v54/calandriello17a/calandriello17a-supp.pdf.

Improved large-scale graph learning through ridge spectral sparsification Distributed sequential sampling for kernel matrix approximation http://proceedings.mlr.press/v54/calandriello17a/calandriello17a-supp.pdf

Reference 8

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Observation c644c380-1650-4619-9776-bf7e471099a1 · outbound

This paper cites http://www.acad.bg/ebook/ml/MITPress- learning.

Improved large-scale graph learning through ridge spectral sparsification http://www.acad.bg/ebook/ml/MITPress- learning

Reference 9

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Observation da8df648-b4dd-4e8c-a3fa-29ff126309c5 · outbound

This paper cites B., Musco, C., and Pachocki, J.

Improved large-scale graph learning through ridge spectral sparsification B., Musco, C., and Pachocki, J

Reference 10

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verified exact
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Observation 38da3e33-cda7-4127-b312-ba49ac9dc07e · outbound

This paper cites Input Sparsity Time Low-Rank Approximation via Ridge Leverage Score Sampling.

Improved large-scale graph learning through ridge spectral sparsification Input Sparsity Time Low-Rank Approximation via Ridge Leverage Score Sampling

Reference 11

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Observation 95c4ee01-583e-4a6e-b8d2-47b69866a455 · outbound

This paper cites Stability of transductive regression algorithms https://cs.nyu.edu/ mohri/pub/str.pdf.

Improved large-scale graph learning through ridge spectral sparsification Stability of transductive regression algorithms https://cs.nyu.edu/ mohri/pub/str.pdf

Reference 12

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Source-reported events for the cited work

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This paper cites Simple and scalable constrained clustering: a generalized spectral method http://proceedings.mlr.press/v51/cucuringu16.pdf.

Improved large-scale graph learning through ridge spectral sparsification Simple and scalable constrained clustering: a generalized spectral method http://proceedings.mlr.press/v51/cucuringu16.pdf

Reference 13

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This paper cites Lectures on Randomized Numerical Linear Algebra.

Improved large-scale graph learning through ridge spectral sparsification Lectures on Randomized Numerical Linear Algebra

Reference 14

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Observation fc682acc-6130-470b-8a20-0c0ac6af2364 · outbound

This paper cites Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering http://dl.acm.org/citation.cfm?id=2627817.2627920.

Improved large-scale graph learning through ridge spectral sparsification Turning big data into tiny data: Constant-size coresets for k-means, pca and projective clustering http://dl.acm.org/citation.cfm?id=2627817.2627920

Reference 15

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This paper cites Frequent Directions : Simple and Deterministic Matrix Sketching.

Improved large-scale graph learning through ridge spectral sparsification Frequent Directions : Simple and Deterministic Matrix Sketching

Reference 16

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Improved large-scale graph learning through ridge spectral sparsification Unresolved cited work

Reference 17

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Observation 49a48329-77c1-4ff2-bcdf-a06c4b7bc4dc · outbound

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Improved large-scale graph learning through ridge spectral sparsification and Mieghem, P

Reference 18

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Improved large-scale graph learning through ridge spectral sparsification Unresolved cited work

Reference 19

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Improved large-scale graph learning through ridge spectral sparsification and Xu, S

Reference 20

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Improved large-scale graph learning through ridge spectral sparsification A nearly-mlogn time solver for SDD linear systems

Reference 21

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Observation e1f799c6-ed75-447b-ae84-a8a8f20ab5f1 · outbound

This paper cites Approximate Gaussian Elimination for Laplacians: Fast, Sparse, and Simple.

Improved large-scale graph learning through ridge spectral sparsification Approximate Gaussian Elimination for Laplacians: Fast, Sparse, and Simple

Reference 22

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Improved large-scale graph learning through ridge spectral sparsification A Framework for Analyzing Resparsification Algorithms

Reference 23

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Improved large-scale graph learning through ridge spectral sparsification R., Gharan, S

Reference 24

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This paper cites Stochastic dominance: Investment decision making under uncertainty http://www.gbv.de/dms/zbw/83445744X.pdf.

Improved large-scale graph learning through ridge spectral sparsification Stochastic dominance: Investment decision making under uncertainty http://www.gbv.de/dms/zbw/83445744X.pdf

Reference 25

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Improved large-scale graph learning through ridge spectral sparsification Graph sparsification approaches for laplacian smoothing http://proceedings.mlr.press/v51/sadhanala16.pdf

Reference 26

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Improved large-scale graph learning through ridge spectral sparsification N., Dorogovtsev, S

Reference 27

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Improved large-scale graph learning through ridge spectral sparsification Graph Sparsification by Effective Resistances

Reference 28

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Improved large-scale graph learning through ridge spectral sparsification Spielman and Shang

Reference 29

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Improved large-scale graph learning through ridge spectral sparsification Freedman's inequality for matrix martingales

Reference 30

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Improved large-scale graph learning through ridge spectral sparsification 2015 , volume =

Reference 31

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Improved large-scale graph learning through ridge spectral sparsification A Tutorial on Spectral Clustering

Reference 32

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Improved large-scale graph learning through ridge spectral sparsification Hitting and commute times in large random neighborhood graphs

Reference 33

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No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

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Improved large-scale graph learning through ridge spectral sparsification Yeung , keywords =

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

source=arxiv_source observed=2026-05-10T00:25:51.723028Z digest=sha256:0f88b8a85e9a52e72a48635acf8a4b85ba361cdf794b8f5d248ecd01d77d0c2f

Observation a7a571a9-08d9-4df3-88b0-08aa6804afca · outbound

This paper cites http://www.aaai.org/Papers/ICML/2003/ICML03-118.pdf Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions.

Improved large-scale graph learning through ridge spectral sparsification http://www.aaai.org/Papers/ICML/2003/ICML03-118.pdf Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-23T11:17:55.486834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

source=arxiv_source observed=2026-05-10T00:25:51.723028Z digest=sha256:63507ea2cd1e7bcf76407f6edfae144f5f7dffe7a58a865b4c7d2eb9795d7884

Pith citing papers

No inbound Pith citation observations are available.