Paper Citation Record · LEDGER

Local linear convergence of gradient methods for overparameterized Gaussian mixtures

As of 17 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2605.30936.

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pith.paper-citation-record.v1
2605.30936 v1

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measured 39 of 39 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-06-28T23:40:46.820775Z

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation 1eecb52b-67b1-45a5-ac63-7537e8e0ddf6 · outbound

This paper cites and Yu, Bin , Date-Added =.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures and Yu, Bin , Date-Added =

Reference 1

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Observation 94adfd63-9b64-4090-bdc7-4165d0846a94 · outbound

This paper cites Bartlett, Philip M.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Bartlett, Philip M

Reference 2

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This paper cites Reconciling modern machine learning practice and the bias-variance trade-off.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Reconciling modern machine learning practice and the bias-variance trade-off

Reference 3

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This paper cites Two models of double descent for weak features.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Two models of double descent for weak features

Reference 4

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Observation 31e0feb4-5d52-443e-86f3-6c7ac9280487 · outbound

This paper cites Local minima structures in gaussian mixture models.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Local minima structures in gaussian mixture models

Reference 5

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Observation 5d53a3e9-52f0-41c7-854f-ba93ab10fb33 · outbound

This paper cites Ten steps of em suffice for mixtures of two gaussians.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Ten steps of em suffice for mixtures of two gaussians

Reference 6

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Observation 3ace3683-1f4f-4161-a832-71c2bf1488ea · outbound

This paper cites Asymptotic normality and optimality in nonsmooth stochastic approximation.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Asymptotic normality and optimality in nonsmooth stochastic approximation

Reference 7

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Observation eb7c1f3c-7ead-448e-bfb6-74871254a1f3 · outbound

This paper cites Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Active manifolds, stratifications, and convergence to local minima in nonsmooth optimization

Reference 8

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Observation 26f633ea-67a1-4045-b9b9-61533bcaac83 · outbound

This paper cites Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Gradient descent with adaptive stepsize converges (nearly) linearly under fourth-order growth

Reference 9

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Unresolved cited work

Reference 10

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This paper cites Drusvyatskiy and A.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Drusvyatskiy and A

Reference 11

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Observation 725b918d-d6bc-4b0c-9fc5-3951dd83d866 · outbound

This paper cites Sharp analysis of expectation-maximization for weakly identifiable models.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Sharp analysis of expectation-maximization for weakly identifiable models

Reference 12

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Observation 00bda9d4-b2fd-4d1b-8d21-dfcfa2b175fb · outbound

This paper cites Singularity, misspecification and the convergence rate of EM.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Singularity, misspecification and the convergence rate of EM

Reference 13

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Observation a290a6c8-a6ca-44a6-bffd-60ebb7a2b7c8 · outbound

This paper cites Identifying active constraints via partial smoothness and prox-regularity.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Identifying active constraints via partial smoothness and prox-regularity

Reference 14

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This paper cites Electronic Journal of Statistics , author =.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Electronic Journal of Statistics , author =

Reference 15

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This paper cites Wainwright, Sivaraman Balakrishnan, and Michael I.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Wainwright, Sivaraman Balakrishnan, and Michael I

Reference 16

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Observation 24ceca4f-e98a-4608-8b0f-43a59b44f678 · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition

Reference 17

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This paper cites Information theory and statistics.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Information theory and statistics

Reference 18

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Observation 3b1639c5-2124-4c24-8ee4-5f708a382361 · outbound

This paper cites The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures The EM Algorithm gives Sample-Optimality for Learning Mixtures of Well-Separated Gaussians

Reference 19

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Observation b6d12af0-16b3-4f3a-b565-c4129253bca8 · outbound

This paper cites The U -Lagrangian of a Convex Function.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures The U -Lagrangian of a Convex Function

Reference 20

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This paper cites Active sets, nonsmoothness, and sensitivity.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Active sets, nonsmoothness, and sensitivity

Reference 21

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures A proximal method for composite minimization

Reference 22

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures A topological property of real analytic subsets

Reference 23

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Proximal points are on the fast track

Reference 24

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Observation d71a8323-f39c-44e4-be83-d6baaf578d66 · outbound

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Gradient methods for minimizing functionals

Reference 25

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Observation 7cbc8d69-f333-4604-918a-dcd702e3db58 · outbound

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Minimization of unsmooth functionals

Reference 26

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Observation 2f9795d2-1624-475d-96f7-098f364d6848 · outbound

This paper cites Mixture densities, maximum likelihood and the EM algorithm.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Mixture densities, maximum likelihood and the EM algorithm

Reference 27

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Identification in parametric models

Reference 28

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Observation c7e3cb7f-ee67-4a08-a630-b673e04ed0bd · outbound

This paper cites Asymptotic behaviour of the posterior distribution in overfitted mixture models.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Asymptotic behaviour of the posterior distribution in overfitted mixture models

Reference 29

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Observation 930706ea-5577-4c1d-8930-03e68682746d · outbound

This paper cites Improved convergence guarantees for learning gaussian mixture models by EM and gradient EM.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Improved convergence guarantees for learning gaussian mixture models by EM and gradient EM

Reference 30

Resolution: verified exact; doi, observed 2026-06-28T23:42:49.029683Z

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This paper cites Asymptotic Behavior of Expected Sample Size in Certain One Sided Tests.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Asymptotic Behavior of Expected Sample Size in Certain One Sided Tests

Reference 31

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Identifiable surfaces in constrained optimization

Reference 32

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Unresolved cited work

Reference 33

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This paper cites Global analysis of expectation maximization for mixtures of two gaussians.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Global analysis of expectation maximization for mixtures of two gaussians

Reference 34

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Local linear convergence of gradient methods for overparameterized Gaussian mixtures Unresolved cited work

Reference 35

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This paper cites Toward global convergence of gradient em for over-parameterized gaussian mixture models.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Toward global convergence of gradient em for over-parameterized gaussian mixture models

Reference 36

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This paper cites Convergence of gradient em on multi-component mixture of gaussians.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Convergence of gradient em on multi-component mixture of gaussians

Reference 37

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This paper cites Electronic Journal of Statistics14(1), 632–660 (2020).

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Electronic Journal of Statistics14(1), 632–660 (2020)

Reference 38

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Observation ee04510f-e9f9-4d94-a4da-d433b2afe4aa · outbound

This paper cites Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures.

Local linear convergence of gradient methods for overparameterized Gaussian mixtures Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures

Reference 39

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