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Paper Citation Record · LEDGER

Learning Curves of Stochastic Gradient Descent in Kernel Regression

As of 10 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2505.22048.

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

pith.paper-citation-record.v1
2505.22048 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:28:34.544204Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-11T03:37:53.098350Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T03:40:53.802548Z

Reference resolution

60 of 60 outbound references displayed

  • verified exact2
  • verified fuzzy52
  • unresolved6
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f87dbfca-ca29-4299-99c5-640172245690 · outbound

This paper cites Advani, Andrew M.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Advani, Andrew M

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.452719Z digest=sha256:5df4ef2206dd70dc47295ae521d2a3e8b66db09e0df6b3a426798629abe5f854

Observation 30c5c8de-51a0-407b-9976-6be5b87b9b3e · outbound

This paper cites Zico Kolter, and Ryan J.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Zico Kolter, and Ryan J

Reference 2

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unresolved
no resolver link, observed 2026-08-07T13:28:30.511154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:28:30.511154Z digest=sha256:0c86b292d66aa454339681f924add490250822b6de2c8c3b327b51babfb8ede4

Observation 528f3247-797e-427f-9f95-da7e71c77c84 · outbound

This paper cites Theory of reproducing kernels.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Theory of reproducing kernels

Reference 3

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation c33e4ece-5189-4a27-8de8-84aa62899604 · outbound

This paper cites On exact computation with an infinitely wide neural net.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On exact computation with an infinitely wide neural net

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.669866Z digest=sha256:3dae2a23d19c8c508ae9ad51f5b1d5822e841243f4af536d509d4cc4037239bb

Observation 0c4cb998-7974-47b1-a020-fde361559cf6 · outbound

This paper cites Non-strongly-convex smooth stochastic approximation with convergence rate o (1/n).

Learning Curves of Stochastic Gradient Descent in Kernel Regression Non-strongly-convex smooth stochastic approximation with convergence rate o (1/n)

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.729889Z digest=sha256:0372cba9ffcf13f578f63269873940b258419e5fd9d19926b9c7e60b52ddf400

Observation 3571e2d6-9788-432a-9373-2f895515bd2f · outbound

This paper cites Benign overfitting in linear regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Benign overfitting in linear regression

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 9a5f717a-e5f9-4c16-bb2f-02bd69f36165 · outbound

This paper cites Generalization in kernel regression under realistic assumptions.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Generalization in kernel regression under realistic assumptions

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.888130Z digest=sha256:c670796caffa4e33ce15fcfdf558be49d8fccaa2bc8a6b61946fd6d59fa0d9ff

Observation f25d4001-f10a-4920-842e-0a63ed843490 · outbound

This paper cites On regularization algorithms in learning theory.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On regularization algorithms in learning theory

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 8143cdc8-0a4c-436d-946d-d6556f42c04c · outbound

This paper cites an unresolved cited work.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:28:31.074894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:28:31.074894Z digest=sha256:5f70bc170a0a1c1ac04f3ea2bfcba4f0aaa402d0a2cb595e1bfdb40595894d58

Observation 36835f13-4464-4e19-aed7-4211036ea78e · outbound

This paper cites Reproducing kernel H ilbert spaces in probability and statistics.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Reproducing kernel H ilbert spaces in probability and statistics

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.137199Z digest=sha256:967470c0ad81b795ae387ee247b7e476b4c64d1eadb3ebb47214ee841ae1aae3

Observation ad746d73-11cb-4ff3-95d2-6f653f35e4d9 · outbound

This paper cites Deep equals shallow for R e LU networks in kernel regimes.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Deep equals shallow for R e LU networks in kernel regimes

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.197802Z digest=sha256:a886231200416730017b28f37aefeddc5a884fd7a09d993be2a3bc10fdbc12c6

Observation 2bef186a-4133-43f5-8d6b-12d399074553 · outbound

This paper cites On the inductive bias of neural tangent kernels.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the inductive bias of neural tangent kernels

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.301352Z digest=sha256:db7222b196c25ef8ffe5c6defde53a0d7ebdb1d4d06874426d00bad8cd870542

Observation ad3fa057-35f6-4925-a59f-9bd080e3299c · outbound

This paper cites Optimal rates for regularization of statistical inverse learning problems.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for regularization of statistical inverse learning problems

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:24.614962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.366940Z digest=sha256:1aad3c2b09a416e0e631eca9052d6def4d4ed39c0dad77df2db02b489be2d7cf

Observation f98ecdf5-e3da-41ff-8185-4f88a0818b24 · outbound

This paper cites Spectrum dependent learning curves in kernel regression and wide neural networks.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Spectrum dependent learning curves in kernel regression and wide neural networks

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.437885Z digest=sha256:5803e923da8980f86c701b8bb0d9b9f40083322c55155c5499d8e6d79a258b89

Observation ff9bd676-7f1f-4e73-a39a-b2127e80e69f · outbound

This paper cites Optimal rates for the regularized least-squares algorithm.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for the regularized least-squares algorithm

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.496474Z digest=sha256:f75296d4a4c2d2fbccdf960161cb9c091da1292bf3a2727148fb245501207890

Observation 2110ad54-d605-4905-abd2-9e9ad93512e1 · outbound

This paper cites On lazy training in differentiable programming.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On lazy training in differentiable programming

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.576613Z digest=sha256:a5ea7f42762696441e132d69387d250b4cbea6d74b49c03d1f8b2e74ab1e7a38

Observation b9d4531b-46a0-43ec-a409-fd43b6ace494 · outbound

This paper cites Generalization error rates in kernel regression: T he crossover from the noiseless to noisy regime.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Generalization error rates in kernel regression: T he crossover from the noiseless to noisy regime

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.670599Z digest=sha256:16ec8fca6ee05ee88c5aad1918c85a8ca2d48c1dd3559de6acaad958c8513eee

Observation f690ef0a-d16d-4560-ac95-5352bfec1efa · outbound

This paper cites Kernel ridge vs.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Kernel ridge vs

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.795526Z digest=sha256:6c9ee8ba3e39e12d53202739ed5859ab7a96b40ea458288129a84c33f0fd71b1

Observation 2123c146-875c-4adf-bf65-4c07d5617bc9 · outbound

This paper cites Nonparametric stochastic approximation with large step-sizes.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Nonparametric stochastic approximation with large step-sizes

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.877769Z digest=sha256:ee7043a82f0d65582c1733ec4153085038d8bfb3acd96d77e970d8c19b318f07

Observation ab863daa-6335-4ad9-b9d2-97c228932d6f · outbound

This paper cites Harder, better, faster, stronger convergence rates for least-squares regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Harder, better, faster, stronger convergence rates for least-squares regression

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:23.025181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.001027Z digest=sha256:2270e1612f6e59a9f6b2d9e3cc2c4b0946541218fab2cafb018697f6e8883a97

Observation a96a35dc-2f31-43eb-968a-f407f50c4a3e · outbound

This paper cites How rotational invariance of common kernels prevents generalization in high dimensions.

Learning Curves of Stochastic Gradient Descent in Kernel Regression How rotational invariance of common kernels prevents generalization in high dimensions

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:22.825690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.070075Z digest=sha256:95707edc52eeac42a083f796bb51fc964027f54075d53ee16cb65cddb925e5ae

Observation 5a8ee295-65b2-4cf0-b1d5-420bb79adfdc · outbound

This paper cites Sobolev norm learning rates for regularized least-squares algorithms.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Sobolev norm learning rates for regularized least-squares algorithms

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:22.647559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.155010Z digest=sha256:e09af00193706c74fdd93c6a2766a409ea18ab502199699cc46b43288e091b20

Observation d370593e-aaf6-4d08-868c-90c7d2f153ad · outbound

This paper cites Notes on spherical harmonics and linear representations of L ie groups.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Notes on spherical harmonics and linear representations of L ie groups

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:22.359300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.219525Z digest=sha256:98bb200209eca9e15ff858bc3d4c574aefa3cb09bca6e12830367e182fd7239a

Observation 857ace10-cc54-45eb-9e4f-cf8abecc3615 · outbound

This paper cites The step decay schedule: A near optimal, geometrically decaying learning rate procedure for least squares.

Learning Curves of Stochastic Gradient Descent in Kernel Regression The step decay schedule: A near optimal, geometrically decaying learning rate procedure for least squares

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:22.211930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.311101Z digest=sha256:d539c0f387367917979f4d4e245c6f90b85801efae1b66f698ae627081d70e49

Observation 01e951e7-dca6-4839-8159-9b1df9642630 · outbound

This paper cites Linearized two-layers neural networks in high dimension.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Linearized two-layers neural networks in high dimension

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:21.928137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.425506Z digest=sha256:3ab9a9d1bfba92233702731019217404799a46fe9b48c673282d1f22d69c94ef

Observation 35a0429f-b9a7-4cc5-964c-6f06d180e18c · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Neural tangent kernel: Convergence and generalization in neural networks

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:21.690736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.498664Z digest=sha256:b670b174d88e69877bcc31941646a4522bdda2a268e6b906cee41c30cf860d23

Observation ed1e9006-3c05-46d1-8f61-d39e28869d91 · outbound

This paper cites Kakade, Rahul Kidambi, Praneeth Netrapalli, and Aaron Sidford.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Kakade, Rahul Kidambi, Praneeth Netrapalli, and Aaron Sidford

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:21.514889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.568408Z digest=sha256:3997846ebdcdbff3a56157729dede91932e358cf1efe915b2d1979a45e25e724

Observation c8dba26c-a0b2-4f59-b161-8abe1d217b45 · outbound

This paper cites On the saturation effect of kernel ridge regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the saturation effect of kernel ridge regression

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:21.294902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.625704Z digest=sha256:6055c475c0ab7be254287efa31e09fa56afa8621474b94a2907aad8912cb4bc6

Observation 07bf811a-4498-46b5-9358-1aab6935fad1 · outbound

This paper cites On the eigenvalue decay rates of a class of neural-network related kernel functions defined on general domains.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the eigenvalue decay rates of a class of neural-network related kernel functions defined on general domains

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:21.098332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.734148Z digest=sha256:dc744acdf3ed2906fbd91dd59e8a1c93f3a0cc824ef0e9cfd8ad2dbb59caf71c

Observation 942a1297-1d5d-4e5f-ac9f-cc87600f89bc · outbound

This paper cites Optimal rates for regularized conditional mean embedding learning.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for regularized conditional mean embedding learning

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:20.878747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.806842Z digest=sha256:84c97fb1ec3940a656c566b75a53d8ad16c54441a54ed5d42ff3d96a95dc6384

Observation c4078bdd-ded4-4b68-be59-8bd5942af7c0 · outbound

This paper cites ridgeless.

Learning Curves of Stochastic Gradient Descent in Kernel Regression ridgeless

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:20.554846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.895575Z digest=sha256:61f589833049d31af75e12abde1e1cfa4a71d6090797ff507afedef1dcaf81fe

Observation 8db7265e-e7f3-4851-be42-960d0602dac1 · outbound

This paper cites On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the multiple descent of minimum-norm interpolants and restricted lower isometry of kernels

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:20.255099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.992544Z digest=sha256:c4a31cc37ba41f57bdfa1f6812ff4dfe8f643a9047a0f8e285a14951626599da

Observation 7e02afed-7326-44f3-aab6-68261169d2aa · outbound

This paper cites Optimal rates for multi-pass stochastic gradient methods.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for multi-pass stochastic gradient methods

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:19.995030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.069966Z digest=sha256:3eaa71b80fa7af56f392d72dd2444d43242df76e9ddf097269fe52cda7e2a38e

Observation 3b155bab-8d45-4071-9453-af4564b99b5a · outbound

This paper cites Optimal rates for spectral algorithms with least-squares regression over H ilbert spaces.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for spectral algorithms with least-squares regression over H ilbert spaces

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:19.727726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.134720Z digest=sha256:806c4efb25ca176ff506ae7720acac2f0206315dd707d0f3fc54d25fcbe15e51

Observation dc7b079e-0aea-4dd8-91ca-d4ec0a950f3e · outbound

This paper cites Statistical optimality of divide and conquer kernel-based functional linear regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Statistical optimality of divide and conquer kernel-based functional linear regression

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:19.466366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.160922Z digest=sha256:cbcda54ac002ee21a20558247e5afca494296b856bfccd306e90ec50a234d668

Observation 03765ffb-98b9-422f-9dd6-c181a74710d1 · outbound

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

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal Rate of Kernel Regression in Large Dimensions

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T13:28:33.246191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:28:33.246191Z digest=sha256:949781dd17f0058817afc998e95d1ac38ecf690519da4ec60df46265f36ab128

Observation 52eb3375-b315-473d-94f8-7c3b43904dad · outbound

This paper cites On the Pinsker bound of inner product kernel regression in large dimensions.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the Pinsker bound of inner product kernel regression in large dimensions

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:28:34.893695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.336493Z digest=sha256:6713e38c0283e4019e7031d0a5fb3975417762567613b1d8ea43d982361ee2bc

Observation 0c866766-f1c9-49fc-8e8e-c7935c76a502 · outbound

This paper cites On the saturation effects of spectral algorithms in large dimensions.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the saturation effects of spectral algorithms in large dimensions

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:19.221380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.399823Z digest=sha256:0c32db101baa978ed715cc0be225d1f6f466100d90f88aa24b0506bd7a966b9f

Observation da2afadb-742d-46d3-a9af-f9740e6800ce · outbound

This paper cites Spectrum of inner-product kernel matrices in the polynomial regime and multiple descent phenomenon in kernel ridge regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Spectrum of inner-product kernel matrices in the polynomial regime and multiple descent phenomenon in kernel ridge regression

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:28:33.451924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:28:33.451924Z digest=sha256:f4b09b304346efefe672470ed2d553ee9ac45aedad755b4a1df7af8fee019c34

Observation 99a27e6a-54a1-45f3-b3b2-ddd91e9bc4d2 · outbound

This paper cites On converse and saturation results for T ikhonov regularization of linear ill-posed problems.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On converse and saturation results for T ikhonov regularization of linear ill-posed problems

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.985935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.521835Z digest=sha256:00a1383e6cb036140c91b25ce0cade7cf1d8ae096a7f11a1f95fbdca19c46493

Observation 9de8fbc2-4dd3-4cc2-9082-db9bc1fac79a · outbound

This paper cites Statistical optimality of stochastic gradient descent on hard learning problems through multiple passes.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Statistical optimality of stochastic gradient descent on hard learning problems through multiple passes

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.851189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.574863Z digest=sha256:5e66748964e64ef49d661f7a55eb4902568f6d5ef7f5d1bb9bec72427ef2ffe5

Observation a372095a-c602-48a4-92c9-0be07e7be7b7 · outbound

This paper cites Acceleration of stochastic approximation by averaging.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Acceleration of stochastic approximation by averaging

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.725063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.633123Z digest=sha256:0f551974a075d1f917b3eb2bc3f55c6ff9dc53edf5a76f786bbd9f31b8082fb5

Observation 3767e793-9fd1-402c-a9fc-90496c5d7288 · outbound

This paper cites Early stopping and non-parametric regression: A n optimal data-dependent stopping rule.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Early stopping and non-parametric regression: A n optimal data-dependent stopping rule

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.505393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.674463Z digest=sha256:499f625c1990fce662aa92db05b3b49eea6841a9c2887ae96c8df94028c8baa5

Observation 2edb3b80-918c-4054-9b97-71085d87da23 · outbound

This paper cites Learning theory estimates via integral operators and their approximations.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Learning theory estimates via integral operators and their approximations

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.325730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.744658Z digest=sha256:a89cb2c7ec0ed96e933098fa33b1634286bced51053dbd4ef96194eb319f217d

Observation 5f877f99-e23d-4c17-877d-48751c70fcde · outbound

This paper cites On Regularization via Early Stopping for Least Squares Regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On Regularization via Early Stopping for Least Squares Regression

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T13:28:33.779225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:28:33.779225Z digest=sha256:a2cdc4d64ce1e830cadf4361e253887526ce266a6eed8d92c27d46e6b0d32c25

Observation 09ae0b85-6498-432a-b760-f6e3e95afe4a · outbound

This paper cites Mercer’s theorem on general domains: O n the interaction between measures, kernels, and RKHS s.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Mercer’s theorem on general domains: O n the interaction between measures, kernels, and RKHS s

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:18.140046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.821943Z digest=sha256:07e9c9e1f7c6791c32f86a6505c53583c4fe8bd7277894eb435b10c6322ad1c6

Observation a551d233-d1a0-44a4-bb7f-97ef2c8bf2d5 · outbound

This paper cites Optimal rates for regularized least squares regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal rates for regularized least squares regression

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:17.867304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.903732Z digest=sha256:a14a663023d6ea3c89181f9fd768091f75b3774f02f2dfe3233f062400b9cd16

Observation f19f2898-a3d2-4d24-9dd8-842e6c8dba64 · outbound

This paper cites an unresolved cited work.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:30:17.679635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.946980Z digest=sha256:79550e36805f1756574a42d39bdb12243bfc3aec788c41108b01bd1312c2a9ed

Observation 7b035188-3105-419f-b443-63ab2666d507 · outbound

This paper cites Benign overfitting in ridge regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Benign overfitting in ridge regression

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:30:17.490646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.979999Z digest=sha256:7217c38cde8b8b445e0726d16c1bea8adedb0b65c21ddcdc53611133868e3bd6

Observation f92bcba8-4079-445b-856f-af9c4911e7fb · outbound

This paper cites Generalization error of spectral algorithms.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Generalization error of spectral algorithms

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:36.168348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.017348Z digest=sha256:3fd58ab070fb96416e57232b057355e295fedd25d586e0fd635ec0c40e892612

Observation 5b1f4d03-a62c-4e13-82ca-b87dd47f6b37 · outbound

This paper cites Last iterate risk bounds of SGD with decaying stepsize for overparameterized linear regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Last iterate risk bounds of SGD with decaying stepsize for overparameterized linear regression

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:36.031601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.051852Z digest=sha256:0b7ae0440fba947ceb0ba77ac38d79adba7a88482b8019cd97e9d5f935231ee5

Observation b40a8229-2cb2-401e-91e0-b5ba7d6e999f · outbound

This paper cites Precise learning curves and higher-order scalings for dot-product kernel regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Precise learning curves and higher-order scalings for dot-product kernel regression

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.867355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.143653Z digest=sha256:be1385e3292314e8d2eb0ed0124d0e40550d69273f85b3c656356a01fd070dda

Observation c8ec7969-6bcc-4243-949b-0433d6f8f018 · outbound

This paper cites Information-theoretic determination of minimax rates of convergence.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Information-theoretic determination of minimax rates of convergence

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.714037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.191799Z digest=sha256:469496a15e65be07a0e92162c93c202b3482b768b5405de078930518ccd8c0ea

Observation 26e0e528-0621-46ff-b940-e1dc69beefec · outbound

This paper cites On early stopping in gradient descent learning.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On early stopping in gradient descent learning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.552255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.222746Z digest=sha256:aea294a2a2d6d2ecd7325ec26a7e858b2807f0bb24bd0b340345308b04f6b023

Observation f5527bde-c280-4b14-86a8-a66475be27b0 · outbound

This paper cites The optimality of (accelerated) SGD for high-dimensional quadratic optimization, 2024 a.

Learning Curves of Stochastic Gradient Descent in Kernel Regression The optimality of (accelerated) SGD for high-dimensional quadratic optimization, 2024 a

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.436305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.264572Z digest=sha256:01283762f590a2fcccdb68b597b7f431273902d0062c0006bcf3c1fd1009a56b

Observation f5c139e7-9eab-4b05-a2a0-3d3753c6f8ab · outbound

This paper cites On the optimality of misspecified spectral algorithms.

Learning Curves of Stochastic Gradient Descent in Kernel Regression On the optimality of misspecified spectral algorithms

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.357042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.301497Z digest=sha256:26ce97720413329628a2591b55c3a374206f3b7b6f69397ad5b0b84d1a2feb21

Observation 2f03f907-533b-4f91-81cd-492e810085ed · outbound

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

Learning Curves of Stochastic Gradient Descent in Kernel Regression Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:28:34.704316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.397426Z digest=sha256:6fa33a82cbf10e012efc3e6d8d723b3840014ec83d8353e5f8af15aadb1d8eac

Observation 8a5df4b9-6ce4-42c3-87de-5823b74e2edf · outbound

This paper cites The phase diagram of kernel interpolation in large dimensions.

Learning Curves of Stochastic Gradient Descent in Kernel Regression The phase diagram of kernel interpolation in large dimensions

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.223797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.436646Z digest=sha256:8446bf641eb70182c7f4ed8fbd1a66acb2e05bb1eadfad3d0478c77cb3a0a1ad

Observation 82f72f4c-062b-4401-abd8-a9a05a68c434 · outbound

This paper cites The benefits of implicit regularization from SGD in least squares problems.

Learning Curves of Stochastic Gradient Descent in Kernel Regression The benefits of implicit regularization from SGD in least squares problems

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.115675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.469821Z digest=sha256:567467ea82d9e73963b6d474c1d1671b545e7191f04d90c687b9278ea8e9d78a

Observation 15acd1e2-6502-4cbd-a4a7-c95a6affbe6c · outbound

This paper cites Benign overfitting of constant-stepsize SGD for linear regression.

Learning Curves of Stochastic Gradient Descent in Kernel Regression Benign overfitting of constant-stepsize SGD for linear regression

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:28:35.003899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.544204Z digest=sha256:ecacc62ffa9a99e5d5a7c6242128cf7e7749d5671bb54e9635dfa45abf230e10

Pith citing papers

Observation 7a9ba9f7-b58d-41c2-95c5-e43999eb3e0b · inbound

Characterizing and Correcting Effective Target Shift in Online Learning cites this paper.

Characterizing and Correcting Effective Target Shift in Online Learning Learning Curves of Stochastic Gradient Descent in Kernel Regression

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:40:53.804286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T03:37:53.098350Z digest=sha256:865c488b33c58176043b0cd2d99ef70a54d3dae6291b2b219e4912994edea206