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Paper Citation Record · LEDGER

Learning Curves of Stochastic Gradient Descent in Kernel Regression

As of 8 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 2026-08-08T06:32:00.761636+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
  • malformed identifier0
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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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.452719Z digest=sha256:52af2268fbc34309f08c22a0943a5d884ad1e87905c9266706f349fc5bf01346

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

Resolution
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
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.669866Z digest=sha256:0b5ceb4f140596222f022924189c5fd52ecbb54cc3903474c695b9644874a03b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.729889Z digest=sha256:ff25f9bcca89cfa101d6bd4438f29de57d13bde70e1ff4eb1306f2f84ca81987

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 2026-08-08T06:32:00.761636+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
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:30.888130Z digest=sha256:5c2d9ffc5881edeb0bd99a5b282c855209930979212a6821a9cbdc37fda0fa73

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 2026-08-08T06:32:00.761636+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
raw_fallback, observed 2026-08-07T13:30:25.630851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.137199Z digest=sha256:d8c1adab19836d225f329de2caa5178949b460cb4b00177a1ac07a0ebb9c7b39

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.197802Z digest=sha256:9bfc62a9b66443fef555a4f36c5b68c1027b93f75d9dea3d1f496a24a5ab6b13

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.301352Z digest=sha256:c6f85c767ba7e5081de89e7a24b7faaf40d5eb99c73cfc8158ec28d79cabf676

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.366940Z digest=sha256:2e4807b899cdde89a6f2db618c7077be0e6c64cc716daecb919b4c91a006cfe5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.437885Z digest=sha256:d298714fe82e93d635a806ec8152728555269817d5b0d33e1b2ce26d12dd9a21

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
raw_fallback, observed 2026-08-07T13:30:24.079500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.496474Z digest=sha256:9352d007bb31298f2a4a985e99878cf935935c4f67361e3a1a2c6c7111e5cd81

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.576613Z digest=sha256:dd944d695f335140b83529992e69bb8507f0252be8a94cc6c287a9a96ac3f265

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.670599Z digest=sha256:079f903bfde3d477a93c969017bf3732fa506cb7d381462d8041a436f9978539

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.795526Z digest=sha256:95faaa279cda05b8eff038e02deb2d54d345c620e60f645a2fa30b4753cc13e3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:31.877769Z digest=sha256:279af60bb5000cd057a4bff4715be7be86dc0b85465f86276831ed4727f92366

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.001027Z digest=sha256:051a7a3b5c214423e035af0da9904e1f115f3ef0c37019227791d1014146de26

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.070075Z digest=sha256:6fa832c8d91cabb0de4f829854b302d60cb70bfeb06e563ce024081c23e97fd6

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.155010Z digest=sha256:408d21dd4bc7b2f3bc3953130e1c080aa79be16b683fef16ac4d7300678387f7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.219525Z digest=sha256:016abca837e2222f3ab403dafd309161b34fd9f432b1241cd2448ff3ccdb3926

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.311101Z digest=sha256:2067db22323470bce587368d022f2da89e2de1a909ec63a74bd96017ba07e28c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.425506Z digest=sha256:3be797fa2b0a82bf7973504627bf882aca2d4f77e41e48f2099e6c65a6600ee6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.498664Z digest=sha256:f36057fd1c14976e63b4f1c9736b8d5930f426a498b745b9a3709b0bddbe03b8

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.568408Z digest=sha256:8bb03017999aa57bf7c4dfc0bc4eac2b8af0562cc441e7396bdb6da16258d970

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.625704Z digest=sha256:058de762488f761b73cf0a07c9fbde1dee1965f2c819c50499cb0c38761264b4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.734148Z digest=sha256:94c04a75aa823ac4f079341a7ac489b63c5fdb7bbdbfe2fece8ba4ffcd292363

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.806842Z digest=sha256:79dced310694be031e643e4348cdc8f3b147f80a2a6d5ae34655a11203a009d7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.895575Z digest=sha256:9d5868c5b62bab9fe2bc4a2e9c3e39b6dd03b436c2931f7985ff907c1e55ed5c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:32.992544Z digest=sha256:6ded80946842dbce4468b3098346aab9c0262dad507154e6632b8d80c99fed51

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.069966Z digest=sha256:7e0d7caa27ed1bc133e8025ec678b8116c0d7f83ecd2a9fadf66f94bb668301e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.134720Z digest=sha256:362b9380085b492e3c1afa482fa85c5fb60e35e1279ff721221912b576a4f189

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.160922Z digest=sha256:6a754aa842b5b58f36a755cfdaa692901bc3f1545ffad7e2b4322b26df97b0d2

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.336493Z digest=sha256:0330bc31ddc30bed5c2e54c1bc48f1c125bde3bec15deb867f86cf2f2d490124

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.399823Z digest=sha256:a09ef808b4aea520c0aa5816b0907d00ac0bdc78ddc8dfa6d74320d5f8cf1e9b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.521835Z digest=sha256:cd838433eebf15fd5ba0646f847dfc934fd4fb1341eda064994a523d8e7716af

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.574863Z digest=sha256:2133a78cd0478fa21a6d2f690f3a9087d0ab15483f4d0c5e829964031546c08b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.633123Z digest=sha256:b6ec70e964b96060719348fcf504ae14d386c9c49c5196f85772a6db95c2e6e1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.674463Z digest=sha256:40394d32f51ca5dc78d2913f7f0d585b19fe0155aa04a3cb8ae18f4686a2e3cf

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.744658Z digest=sha256:aa5113cc3f13c6048cab382a1e9404d04811d6ad5dfa128a559373c0e7e8a8cb

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.821943Z digest=sha256:cf54f2d502e3484ce769a0aa44a2292c2e571dafb51d635dbc7df1ba692d09df

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.903732Z digest=sha256:13a907c358389153b1f6105f42f617e7d6c74ed567adc007e57411d09c581865

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.946980Z digest=sha256:f568f208e6e59c21e972e9e6e745ec03718a8b88157ec7133e3bb1323a1aa62d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:33.979999Z digest=sha256:06bd28f67f964c5e5263ae03885e20ea2c9a26c3f56360e42d43c67015679ea5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.017348Z digest=sha256:706511cca5974a792ce8586a4d30ca84d1b2c761ea66755db8d699f3e875228c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.051852Z digest=sha256:3e4bb0e5a404cd37c3b55c3d8bc85bcd24ff78cb8d29559d4446c713f88022aa

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.143653Z digest=sha256:b336ea2a0383b6b9c04dd6961a07bb9d642daa9581b48bbc9d0cca80b73f4d95

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.191799Z digest=sha256:fb3f294dd5987841ec03eb16ad047cbd39b279b87d49a03764a08a48d7d70f42

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.222746Z digest=sha256:c97340db68dc4fb8999b87edcd3612e8339e93d42bb19a72f45cfd3a8ab9cd1b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.264572Z digest=sha256:5a1dd374ae69c5b622ece64d63bdb15c377ac3182524663573473e5d9a8cb8ed

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.301497Z digest=sha256:0b799a8077898806a83d829f09a8a26ed073ae36fe7ead9071059080f3ca63b1

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.397426Z digest=sha256:2153f49da152e2a1aa872ac1d988c21c2ae237d8e9a49dec86d2a06cca9e202f

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.436646Z digest=sha256:85a2ed60ab6ddb35a3434a0f6175aa3a0b86928a5f3fa88928ece11a8a996bfc

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.469821Z digest=sha256:ef04ed2254f7f091eb78bd0716882a94ce9b4258750b70eb6a17efcf0f818e32

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T13:28:34.544204Z digest=sha256:1cf69650cb903dd5501b873b639403964d7299a8fe171c02ea8f694c72a3bf54

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T03:37:53.098350Z digest=sha256:9e8ca21d1fd39c99a958726bfc084c4f3db370842adc099fd7fe99534434276d