Paper Citation Record · LEDGER

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2608.06250.

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pith.paper-citation-record.v1
2608.06250 v1

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measured 43 of 43 reference resolution

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43 of 43 outbound references displayed

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Outbound references

Observation c40802b4-74d6-490b-9ce8-b4a5f78ba37a · outbound

This paper cites Support vector machines and linear regression coincide with very high-dimensional features.Advances in Neural Information Processing Systems, 34: 4907–4918, 2021.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Support vector machines and linear regression coincide with very high-dimensional features.Advances in Neural Information Processing Systems, 34: 4907–4918, 2021

Reference 1

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Observation ccbff15e-dad5-41d3-aac1-6d8e5b3461b9 · outbound

This paper cites Early stopping and polynomial smoothing in regression with reproducing kernels.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Early stopping and polynomial smoothing in regression with reproducing kernels

Reference 2

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Observation 1a79050b-b8bc-4c1e-907a-a879af5cabee · outbound

This paper cites MIT press, 2024.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification MIT press, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T11:33:58.080504Z

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Observation e04406eb-ddbf-47b9-aadd-09a9ac96a289 · outbound

This paper cites Bartlett, Olivier Bousquet, and Shahar Mendelson.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Bartlett, Olivier Bousquet, and Shahar Mendelson

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:10.421612Z

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Observation d2052fe2-022f-4f97-ab74-19ff1da006e5 · outbound

This paper cites Convexity, classification, and risk bounds.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Convexity, classification, and risk bounds

Reference 5

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Observation 4e659b3b-cd39-4987-bf2c-e9e23dd24221 · outbound

This paper cites Benign overfitting in linear regression.Proceedings of the National Academy of Sciences, 117(48):30063–30070, 2020.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Benign overfitting in linear regression.Proceedings of the National Academy of Sciences, 117(48):30063–30070, 2020

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:10.240412Z

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Observation 586e7862-c984-4216-98ff-6f6803b154ef · outbound

This paper cites Two models of double descent for weak features.SIAM Journal on Mathematics of Data Science, 2(4):1167–1180, 2020.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Two models of double descent for weak features.SIAM Journal on Mathematics of Data Science, 2(4):1167–1180, 2020

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T11:33:58.606272Z

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Observation 760c1cf9-3d8e-415f-9517-7da329791291 · outbound

This paper cites Boosting With the L2 Loss.Journal of the American Statistical Associ- ation, 98(462):324–339, 2003.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Boosting With the L2 Loss.Journal of the American Statistical Associ- ation, 98(462):324–339, 2003

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:10.030371Z

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Observation d19bd4c7-0dae-448f-9005-240b40bd1529 · outbound

This paper cites Risk bounds for over-parameterized maximum margin classification on sub-gaussian mixtures.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Risk bounds for over-parameterized maximum margin classification on sub-gaussian mixtures

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.834000Z

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Observation e8a66185-2214-42a2-93c0-9a941eac3988 · outbound

This paper cites Caponnetto and E.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Caponnetto and E

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.579164Z

Source-reported events for the cited work

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Observation 394ee276-6a41-4e4f-b968-f22cf5bf7b8c · outbound

This paper cites Chatterji and Philip M.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Chatterji and Philip M

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.321373Z

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Observation c21a6b40-fe85-4c4d-9c5a-a7f024b8b677 · outbound

This paper cites A model of double descent for high- dimensional binary linear classification.Information and Inference: A Journal of the IMA, 11(2): 435–495, 2022.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification A model of double descent for high- dimensional binary linear classification.Information and Inference: A Journal of the IMA, 11(2): 435–495, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:09.140042Z

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Observation 45b56ba1-5165-4e32-8e96-cc6796246d26 · outbound

This paper cites Universality of Benign Overfitting in Binary Linear Classification.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Universality of Benign Overfitting in Binary Linear Classification

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:34:03.392749Z

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Observation 2634be98-f7e4-4279-8465-f845f56298f0 · outbound

This paper cites Springer Series in Statistics.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Springer Series in Statistics

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.900150Z

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Observation 1be7d3fc-4c23-4247-bc17-377abd361730 · outbound

This paper cites Surprises in high-dimensional ridgeless least squares interpolation.Annals of statistics, 50(2):949, 2022.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Surprises in high-dimensional ridgeless least squares interpolation.Annals of statistics, 50(2):949, 2022

Reference 15

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Observation 6513399c-15de-40da-afe2-e2be49128398 · outbound

This paper cites On the proliferation of support vectors in high dimensions.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification On the proliferation of support vectors in high dimensions

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.673427Z

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Observation 41cb9622-acc2-4a3e-a5a3-2bb034e55dfc · outbound

This paper cites The implicit bias of gradient descent on nonseparable data.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The implicit bias of gradient descent on nonseparable data

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.422092Z

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Observation aabe32b9-1f4f-462b-8ab9-29690dd43f08 · outbound

This paper cites On the precise error analysis of support vector machines.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification On the precise error analysis of support vector machines

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:08.217577Z

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Observation ec28e6ee-69e2-4858-b781-93df49ca1f6f · outbound

This paper cites The statistical complexity of early-stopped mirror descent.Information and Inference: A Journal of the IMA, 12(4):3010–3041, 2023.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The statistical complexity of early-stopped mirror descent.Information and Inference: A Journal of the IMA, 12(4):3010–3041, 2023

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.973466Z

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Observation e9f123aa-9ace-4b97-a674-e94dfa19cb87 · outbound

This paper cites Analytic study of double descent in binary classification: The impact of loss.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Analytic study of double descent in binary classification: The impact of loss

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.741732Z

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Observation 6fce4938-fb3a-4bc1-8f27-26eeee075e75 · outbound

This paper cites Concentration inequalities and moment bounds for sample covariance operators.Bernoulli, pages 110–133, 2017.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Concentration inequalities and moment bounds for sample covariance operators.Bernoulli, pages 110–133, 2017

Reference 21

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Observation 247ea923-eaeb-433c-bc42-11b566d21a0c · outbound

This paper cites Optimal rates for multi-pass stochastic gradient methods.Journal of Machine Learning Research, 18(97):1–47, 2017.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Optimal rates for multi-pass stochastic gradient methods.Journal of Machine Learning Research, 18(97):1–47, 2017

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.499605Z

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Observation 57fb5bf3-fa12-46a5-8761-779efc4bcccd · outbound

This paper cites The role of regularization in classification of high-dimensional noisy gaussian mixture.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The role of regularization in classification of high-dimensional noisy gaussian mixture

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.241197Z

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Observation fcb2c9e8-3b93-4000-9324-c283de8bb1cb · outbound

This paper cites The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The generalization error of max-margin linear classifiers: Benign overfitting and high dimensional asymptotics in the overparametrized regime

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:07.029145Z

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Observation 7135ee31-b549-423c-aeb2-d0eda6bf1872 · outbound

This paper cites Harmless interpolation of noisy data in regression.IEEE Journal on Selected Areas in Information Theory, 1(1):67–83, 2020.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Harmless interpolation of noisy data in regression.IEEE Journal on Selected Areas in Information Theory, 1(1):67–83, 2020

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.812404Z

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Observation d136cd30-1c92-48e0-b025-7ac44c03dda8 · outbound

This paper cites Classification vs regression in overparameterized regimes: does the loss function matter?J.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Classification vs regression in overparameterized regimes: does the loss function matter?J

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.600916Z

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Observation 9b7bd08e-c034-440e-a6ac-b32b71672925 · outbound

This paper cites Statistical optimality of stochastic gradient descent on hard learning problems through multiple passes.Advances in Neural Information Processing Systems, 31, 2018.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Statistical optimality of stochastic gradient descent on hard learning problems through multiple passes.Advances in Neural Information Processing Systems, 31, 2018

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.385284Z

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Observation ea9ca608-d4d8-4e98-aa16-266afae98a9b · outbound

This paper cites Early stopping and non-parametric regression: an optimal data-dependent stopping rule.The Journal of Machine Learning Research, 15(1):335–366, 2014.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Early stopping and non-parametric regression: an optimal data-dependent stopping rule.The Journal of Machine Learning Research, 15(1):335–366, 2014

Reference 28

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This paper cites The Impact of Regularization on High-dimensional Logistic Regression.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The Impact of Regularization on High-dimensional Logistic Regression

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:06.130402Z

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Observation 65076946-84e3-4a62-aa1c-a842786e2e46 · outbound

This paper cites The performance analysis of generalized margin maximizers on separable data.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The performance analysis of generalized margin maximizers on separable data

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:05.884893Z

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Observation c329f657-98b1-4b08-b6cb-dc7772989f12 · outbound

This paper cites Gradient methods never overfit on separable data.Journal of Machine Learning Research, 22(85):1–20, 2021.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Gradient methods never overfit on separable data.Journal of Machine Learning Research, 22(85):1–20, 2021

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:05.555511Z

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Observation 522cedd5-8d11-4431-937f-4e6042bdee60 · outbound

This paper cites The implicit bias of gradient descent on separable data.Journal of Machine Learning Research, 19(70):1–57, 2018.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification The implicit bias of gradient descent on separable data.Journal of Machine Learning Research, 19(70):1–57, 2018

Reference 32

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Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Connecting optimization and regularization paths

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:05.278037Z

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Observation 4ffaefa0-96e1-4ceb-a002-219e27788273 · outbound

This paper cites Cand` es.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Cand` es

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:05.037042Z

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Observation decd8784-5bf8-46f5-91c5-1daa030606ab · outbound

This paper cites Benign overfitting in ridge regression.Journal of Machine Learning Research, 24(123):1–76, 2023.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Benign overfitting in ridge regression.Journal of Machine Learning Research, 24(123):1–76, 2023

Reference 35

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Observation 0d98f6b4-000c-44a8-ac3b-9f70692a6485 · outbound

This paper cites Benign Overfitting and the Geometry of the Ridge Regression Solution in Binary Classification.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Benign Overfitting and the Geometry of the Ridge Regression Solution in Binary Classification

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T11:34:02.270980Z

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Observation 013056b0-bc6e-44e3-845c-904f7c81ad9f · outbound

This paper cites Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization.SIAM Journal on Mathematics of Data Science, 4(1):260–284, 2022.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization.SIAM Journal on Mathematics of Data Science, 4(1):260–284, 2022

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:04.837180Z

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Observation 34ec55bb-fa66-4a8a-a422-9547dd17bdfd · outbound

This paper cites Early stopping for kernel boosting algorithms: A general analysis with localized complexities.IEEE Transactions on Information Theory, 65(10): 6685–6703, 2019.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Early stopping for kernel boosting algorithms: A general analysis with localized complexities.IEEE Transactions on Information Theory, 65(10): 6685–6703, 2019

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:04.602994Z

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Observation bae79b10-d417-4905-ad65-812627274d84 · outbound

This paper cites Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T11:34:02.687791Z

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Observation e10bd25c-1a15-4ff3-b7e4-ade4468c630e · outbound

This paper cites Bartlett, Matus Telgarsky, and Bin Yu.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Bartlett, Matus Telgarsky, and Bin Yu

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:04.340330Z

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Observation aaa92d12-0477-4df7-8aef-a576cc398079 · outbound

This paper cites On Early Stopping in Gradient Descent Learning.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification On Early Stopping in Gradient Descent Learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:04.111414Z

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Observation fbb50e35-2fef-41b7-a2bd-250f1aaea724 · outbound

This paper cites Z |Tu|/ρ −|Tu|/ρ |t|fT ∗ (t)dt # ≤ 1−2p√ 2π∥µ∥ Σ−1 E.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Z |Tu|/ρ −|Tu|/ρ |t|fT ∗ (t)dt # ≤ 1−2p√ 2π∥µ∥ Σ−1 E

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:03.853247Z

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Observation 297a7737-347d-4d5f-aa2a-05e0908bce95 · outbound

This paper cites Triangle inequality.

Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Triangle inequality

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:34:03.627767Z

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