Paper Citation Record · LEDGER

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression

As of 16 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2502.09106.

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

pith.paper-citation-record.v1
2502.09106 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:45:01.954179Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:08:12.196409Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:16:03.099041Z

Reference resolution

51 of 51 outbound references displayed

verified exact1
verified fuzzy15
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4760d784-3186-45c1-9e9f-0a8ab2a3a1d4 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 1

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Observation 0d2e83d8-bc44-4b4b-8fcc-2628f68f6aa4 · outbound

This paper cites S., Hu, W., Li, Z., Salakhutdinov, R.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression S., Hu, W., Li, Z., Salakhutdinov, R

Reference 2

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Observation 1f14731c-9479-4cde-bcf6-4ccd6bc164df · outbound

This paper cites A., Suzuki, T., Wang, Z., Wu, D., & Yang, G.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression A., Suzuki, T., Wang, Z., Wu, D., & Yang, G

Reference 3

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Observation 9a68ff27-9262-4dc2-bf18-e4972efb1e29 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 4

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 5

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Observation c6fdcc2d-1076-4ac0-88a2-62535bb6a5da · outbound

This paper cites L., Long, P.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression L., Long, P

Reference 6

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Observation 67631969-1c44-430b-a417-5cc4e3d7e723 · outbound

This paper cites L., Montanari, A., & Rakhlin, A.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression L., Montanari, A., & Rakhlin, A

Reference 7

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Observation 91bbeae8-a30f-48af-a00b-2e7339e7e626 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 8

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Observation 599a1f9e-4835-4424-a1d2-0725d5617586 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 9

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Observation 40f9a9d2-b095-4a64-a33d-d209e8e0a15d · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 10

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Observation 59f46074-dd84-4d79-b353-30f07fd49667 · outbound

This paper cites Learning Curves for SGD on Structured Features.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Learning Curves for SGD on Structured Features

Reference 11

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This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 12

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Observation 9df81968-883b-4d23-8079-f1fbd7975416 · outbound

This paper cites T., & Hall, P.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression T., & Hall, P

Reference 13

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Observation 223633e3-e139-453f-95b7-c47eafb8389c · outbound

This paper cites J., & Tao, T.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression J., & Tao, T

Reference 14

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Observation c336bfb8-426f-467a-8846-9a5859b5baef · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 15

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Observation 1822e000-f46f-45c9-9d25-e515b72b8488 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 16

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Observation 33015d8e-8ef4-4b3f-9cf1-089f6891834c · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 17

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Observation ad43fd5e-0cd9-4c05-beea-776e282fe7ab · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 18

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Observation e94491b4-c846-42fa-a821-b87b040ea6bf · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 19

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Observation f4987d35-4ce2-4f54-ba79-6f9a8c0a4ebe · outbound

This paper cites M., Kidambi, R., & Netrapalli, P.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression M., Kidambi, R., & Netrapalli, P

Reference 20

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Observation d03d6019-a072-4995-8cfb-d1e5f6683541 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 21

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Observation 611b49bb-656c-4bc0-a4f8-e99b7c755293 · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 22

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Observation 472e7094-c151-4b8e-b8f0-ab1f190d34a3 · outbound

This paper cites E., Bhojanapalli, S., Neyshabur, B., & Srebro, N.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression E., Bhojanapalli, S., Neyshabur, B., & Srebro, N

Reference 23

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Observation 410ac9e7-99d4-4a61-8f8e-1302840b6196 · outbound

This paper cites Z., Wei, C., Lee, J., & Ma, T.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Z., Wei, C., Lee, J., & Ma, T

Reference 24

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Observation 7a7026c0-6ac2-479d-842b-8da8605d3b67 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 25

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Observation c19fbc7e-b62c-48da-a41e-4ab165aad260 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 26

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Observation 45c10b88-dd16-43cf-ab98-ebdf61f365c0 · outbound

This paper cites M., Kidambi, R., Netrapalli, P., & Sidford, A.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression M., Kidambi, R., Netrapalli, P., & Sidford, A

Reference 27

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This paper cites Scaling Laws for Neural Language Models.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Scaling Laws for Neural Language Models

Reference 28

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 29

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Observation 8ac3e478-bbe8-4e5c-94d3-040fe6c75369 · outbound

This paper cites Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit

Reference 30

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Observation 5359dc43-2dea-49a0-a6f6-f1c5a2655f87 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Enhanced Convolutional Neural Tangent Kernels

Reference 31

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 32

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Observation 86283d40-f194-4b74-84ef-ac3d00eadcf6 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 33

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc2a2651-5392-4f39-99dc-c690e34094dc · outbound

This paper cites M., Bartlett, P., & Lee, J.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression M., Bartlett, P., & Lee, J

Reference 34

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Source-reported events for the cited work

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Observation 7defaae6-598d-4d1d-9add-11fa67264a00 · outbound

This paper cites Optimal Rate of Kernel Regression in Large Dimensions.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Optimal Rate of Kernel Regression in Large Dimensions

Reference 35

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:45:02.350483Z

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Observation dbf3fdeb-eb73-4127-b580-e6a45a56d001 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 37

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Observation 871480ae-d2cd-4978-bf12-d729d99cb580 · outbound

This paper cites Neural Networks Efficiently Learn Low-Dimensional Representations with SGD.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Neural Networks Efficiently Learn Low-Dimensional Representations with SGD

Reference 38

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 39

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Observation d1737fcc-0956-4a29-8a13-9a639f1bd7b6 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression J., & Yu, B

Reference 40

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Source-reported events for the cited work

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Observation ecb0b65d-718d-4a7b-8990-7e7a8cd1c534 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 41

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Source-reported events for the cited work

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Observation 71f24c24-6017-4cc8-be76-d3236fa87fdd · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression V., Pillaud-Vivien, L., & Flammarion, N

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:45:02.274192Z

Source-reported events for the cited work

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Observation c7d8b43d-6a26-4a71-8552-82186aabc495 · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ec39802a-18ec-4582-8920-3d154927581a · outbound

This paper cites Pruning is Optimal for Learning Sparse Features in High-Dimensions.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Pruning is Optimal for Learning Sparse Features in High-Dimensions

Reference 44

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Observation 39efac50-ca79-40a1-ab8a-8718c418bbab · outbound

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Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:45:02.240221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1639e466-ee7a-43ca-b0ca-291137d81f9a · outbound

This paper cites D., Moroshko, E., Savarese, P., Golan, I.,.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression D., Moroshko, E., Savarese, P., Golan, I.,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:45:02.224508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation be46a56a-2dc3-4310-bc12-ee872b4f7e2b · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:45:02.209155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2a13ff9d-ad19-4dee-8c53-2802fc03cdf9 · outbound

This paper cites Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions

Reference 48

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Source-reported events for the cited work

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Observation 1154d0e6-ff83-4c15-a2b3-b583cd9ce1eb · outbound

This paper cites The Optimality of (Accelerated) SGD for High-Dimensional Quadratic Optimization.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression The Optimality of (Accelerated) SGD for High-Dimensional Quadratic Optimization

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T22:45:01.945278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13e6e460-765c-4060-98ab-6f1e3c761583 · outbound

This paper cites P., & Kakade, S.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression P., & Kakade, S

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:45:02.193418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1aab2e70-feee-4444-af58-ad67da125719 · outbound

This paper cites an unresolved cited work.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:45:02.177887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

Observation f2163b9f-3c66-4d74-9e2e-4b954d19bc32 · inbound

Mild Over-Parameterization Benefits Asymmetric Tensor PCA cites this paper.

Mild Over-Parameterization Benefits Asymmetric Tensor PCA Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.