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 2026-08-07T06:34:17.273281+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

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External citation measurements

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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; raw_fallback, observed 2026-08-07T13:30:27.955091Z

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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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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; raw_fallback, observed 2026-08-07T13:30:27.635726Z

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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; raw_fallback, observed 2026-08-07T13:30:27.187460Z

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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; raw_fallback, observed 2026-08-07T13:30:26.974856Z

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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; raw_fallback, observed 2026-08-07T13:30:26.475062Z

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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; raw_fallback, observed 2026-08-07T13:30:26.184888Z

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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; raw_fallback, observed 2026-08-07T13:30:25.935058Z

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

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

Reference 9

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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

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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; raw_fallback, observed 2026-08-07T13:30:25.242607Z

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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; raw_fallback, observed 2026-08-07T13:30:24.855018Z

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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

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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; raw_fallback, observed 2026-08-07T13:30:24.274846Z

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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

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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; raw_fallback, observed 2026-08-07T13:30:23.933431Z

Source-reported events for the cited work

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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; raw_fallback, observed 2026-08-07T13:30:23.774765Z

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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; raw_fallback, observed 2026-08-07T13:30:23.465292Z

Source-reported events for the cited work

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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; raw_fallback, observed 2026-08-07T13:30:23.218226Z

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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

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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

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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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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