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Paper Citation Record · LEDGER

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations

As of 15 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:1908.10935.

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

pith.paper-citation-record.v1
1908.10935 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:39:53.611050Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T03:15:47.958266Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T00:31:18.035990Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact4
  • verified fuzzy20
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ae85262-90c5-44a1-af86-84dfd966e2af · outbound

This paper cites Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate gaussian mixture models.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate gaussian mixture models

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.473828Z digest=sha256:b607d1c21bf367c0d6dc777a284d10552004a80554423dcd680a0c66a0a3b889

Observation 6eb913c6-b5b9-4828-bc6b-97e81519fb72 · outbound

This paper cites Statistical guarantees for the EM algorithm: From population to sample-based analysis.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Statistical guarantees for the EM algorithm: From population to sample-based analysis

Reference 2

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no resolver link, observed 2026-08-14T10:39:53.479158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.479158Z digest=sha256:58d41e263b4cfc4aea59277409578b9da6b14ec50f9617e9aed395ed3fbb7404

Observation 63f8fdc7-0588-482a-abb4-9ca434473b79 · outbound

This paper cites Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval

Reference 3

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raw_fallback, observed 2026-08-14T10:39:54.021680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.483585Z digest=sha256:ffbaecf87f9e2fdee6cf9317de8722bfc8fa483dafd192c4b026fc94b3959bc0

Observation 2b408e5f-bb66-44d0-893a-a3d2e46fdac2 · outbound

This paper cites Trust region methods , volume 1.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Trust region methods , volume 1

Reference 4

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raw_fallback, observed 2026-08-14T10:39:54.010705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.488218Z digest=sha256:2b99d2fc0bffef34b2d7f2021ea1e7c437e63a2c658413266fc37f731f6ce148

Observation 708b1de1-d72e-4be3-bca2-d0745ecc1e76 · outbound

This paper cites Cai, Zongming Ma, and Yihong Wu.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Cai, Zongming Ma, and Yihong Wu

Reference 5

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raw_fallback, observed 2026-08-14T10:39:53.999473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.491997Z digest=sha256:5e367c99e2d8860d9b6210d1def9aeb20b3482a97694fc0d3a5e664daaf6b139

Observation f4532618-8cd2-482a-9d01-d6b4f2cf3137 · outbound

This paper cites Singularity, Misspecification, and the Convergence Rate of EM.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Singularity, Misspecification, and the Convergence Rate of EM

Reference 6

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unresolved
no resolver link, observed 2026-08-14T10:39:53.495790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.495790Z digest=sha256:ab6ed00107b534b08e273675bbc0945d3d74fbea7bc7c421f0a01bdbe005b20e

Observation 978e8a92-bed7-49f3-8b9d-d372266fd9f3 · outbound

This paper cites Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models

Reference 7

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verified exact
local_arxiv, observed 2026-08-14T10:39:53.715023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.499951Z digest=sha256:dd23962bb01ed905a29056ff8627752e1c2d71ad88fe854583339dbabb81566e

Observation 3076b55f-569a-4fdd-b523-1114555776e7 · outbound

This paper cites Maximum likelihood from incomplete data via the EM algorithm.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Maximum likelihood from incomplete data via the EM algorithm

Reference 8

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raw_fallback, observed 2026-08-14T10:39:53.988454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.504011Z digest=sha256:5cc1e49b4d755e8dbf4c2a1fdb065defcea5bdca40d38e646280f4676a1b9214

Observation 8b208a99-bcad-4451-8dc6-27c9402796dd · outbound

This paper cites Local operator theory, random matrices and B anach spaces.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Local operator theory, random matrices and B anach spaces

Reference 9

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raw_fallback, observed 2026-08-14T10:39:53.977135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.507839Z digest=sha256:da4dee522b20dfbdf8f845e8823606fdf158977cb47a96aa454344cdde7ea1a8

Observation 663a9914-9177-4a5d-b93c-1f33c65e780e · outbound

This paper cites Ten steps of EM suffice for mixtures of two G aussians.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Ten steps of EM suffice for mixtures of two G aussians

Reference 10

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raw_fallback, observed 2026-08-14T10:39:53.966124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.511206Z digest=sha256:34dd227f1743b13811b3883521ca7ea314b1fa1b6ae809698d69af5eb2138b71

Observation ce337b71-bfc9-4e20-8632-f6ea39db6835 · outbound

This paper cites an unresolved cited work.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Unresolved cited work

Reference 11

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raw_fallback, observed 2026-08-14T10:39:53.954416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.514683Z digest=sha256:85dd1bd585bf9b36c954cd8d7f10f0b5ab9c51ac17a7a0ee072dba142ac72921

Observation 553c4508-213e-476d-a713-16816c24c695 · outbound

This paper cites On the rate of convergence in wasserstein distance of the empirical measure.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations On the rate of convergence in wasserstein distance of the empirical measure

Reference 12

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raw_fallback, observed 2026-08-14T10:39:53.942705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.519443Z digest=sha256:e5c2e8772bc23055a6c9d9631275f09ed24ea459d0d59edafc589a3223131bce

Observation a3974d9d-2e18-4ccf-abbd-6bcd7a882988 · outbound

This paper cites an unresolved cited work.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-14T10:39:53.931195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.522836Z digest=sha256:c342152e681c00f02751a53afd8f0e40ec47adda934f2ed1859aa318e5102af9

Observation 57f1c1c8-7555-4900-a33c-8d86d3b2d357 · outbound

This paper cites Optimal rates for finite mixture estimation.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Optimal rates for finite mixture estimation

Reference 14

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verified exact
local_arxiv, observed 2026-08-14T10:39:53.699346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.526290Z digest=sha256:0e82d2a0021f25c9ad3593b6742cdc191190e62b4de4b60b1872de262c2741bf

Observation ea5e5bf0-7bf3-42f9-9469-e4dfef82f078 · outbound

This paper cites Convergence rates of parameter estimation for some weakly identifiable finite mixtures.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Convergence rates of parameter estimation for some weakly identifiable finite mixtures

Reference 15

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raw_fallback, observed 2026-08-14T10:39:53.919742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.530101Z digest=sha256:2cb757919630539818aa105d21afe2642e17232faf9336c3a3fd24ba6dbf0112

Observation 2fb4b4d9-8faa-4200-9bd0-0688a12b6fef · outbound

This paper cites Ingster and I.A.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Ingster and I.A

Reference 16

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raw_fallback, observed 2026-08-14T10:39:53.908171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.533381Z digest=sha256:a7d4fa9564f1d42a95ac0ee30c19fa8cebe382245bb4ec997fb3ab77fac5df9d

Observation defc50cc-c371-4cc5-b739-a096f07d306f · outbound

This paper cites Local maxima in the likelihood of G aussian mixture models: Structural results and algorithmic consequences.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Local maxima in the likelihood of G aussian mixture models: Structural results and algorithmic consequences

Reference 17

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no resolver link, observed 2026-08-14T10:39:53.536603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.536603Z digest=sha256:2a6ca1811cf93c9e0e827779a626fd2ae170e9be206ebcdde8189052fe32ea7f

Observation 110d422b-13c5-48e1-88ff-1b3c3c4fa743 · outbound

This paper cites Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Global Convergence of EM Algorithm for Mixtures of Two Component Linear Regression

Reference 18

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no resolver link, observed 2026-08-14T10:39:53.540945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.540945Z digest=sha256:adb0f0aea23a105920a777b66036e048e75e74fa5511169b384712c23150d77c

Observation b5fd964a-47a7-425d-8bb6-954924f55a19 · outbound

This paper cites Choosing initial values for the EM algorithm for finite mixtures.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Choosing initial values for the EM algorithm for finite mixtures

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.890465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.544826Z digest=sha256:c9b6229fe1212c8f8c8fdfa08482561980c1f9e77f4640f72f388fcbc1b14ff2

Observation 22115801-4bdb-48d1-a5aa-7e15b663af58 · outbound

This paper cites Laurent and P.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Laurent and P

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.878362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.548259Z digest=sha256:007e0b3a7bf66b431d6d79f70d694b8ad7fcd694d2aae1acc76b60ae3073eb94

Observation df4de3a5-b62a-4438-a9b2-9dde80ec66a1 · outbound

This paper cites Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Statistical and Computational Guarantees of Lloyd's Algorithm and its Variants

Reference 21

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no resolver link, observed 2026-08-14T10:39:53.551650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.551650Z digest=sha256:be582049a41d9cc7aadd5f1b6f41c11022bf86caeea30bc6b891a862cbd9fc1d

Observation 4a4d94b6-af11-471f-976f-8984fe3f80a5 · outbound

This paper cites The landscape of empirical risk for nonconvex losses.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations The landscape of empirical risk for nonconvex losses

Reference 22

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raw_fallback, observed 2026-08-14T10:39:53.866005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.555173Z digest=sha256:cc123f9ab0dfa9fc288bccbd3a9213171b599730e2e97a447e3fe8581956e1f0

Observation 3cae0bc5-1ab1-4cd6-b2f2-51c038c7a617 · outbound

This paper cites Sharp optimal recovery in the two-component Gaussian Mixture Model.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Sharp optimal recovery in the two-component Gaussian Mixture Model

Reference 23

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verified exact
local_arxiv, observed 2026-08-14T10:39:53.664058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.558952Z digest=sha256:a357d2fe794a4932797d3658fcca9ec463df885b2016623134086d93c599d5aa

Observation 604576eb-96fc-42d5-9c28-a13ce85ff118 · outbound

This paper cites Dissipation of information in channels with input constraints.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Dissipation of information in channels with input constraints

Reference 24

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raw_fallback, observed 2026-08-14T10:39:53.854232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.563890Z digest=sha256:0383d91b6db02a52c6ce8b09be9f1b8f00581bc4ec7ac359e9801d03bed9730a

Observation cbbb5f2b-5a96-412c-ac00-61e061ddb796 · outbound

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

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Mixture densities, maximum likelihood and the EM algorithm

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.842977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.570184Z digest=sha256:b53cddf0b73ddfb9c57d6ecdb419d013b9624920e38ff51bea2d56462feed037

Observation 94fb9ce1-54f4-4004-ad1c-b37967fc94d9 · outbound

This paper cites An introduction to maximum-likelihood methods in cryo- EM.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations An introduction to maximum-likelihood methods in cryo- EM

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.831193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.574020Z digest=sha256:934bb7336a91680bae2b629546e72ed525950c7762d1c82c7eda6f2a1929b18a

Observation 5e6e3bef-0760-4f0c-aa47-512db1b5ee5a · outbound

This paper cites Empirical processes with applications to statistics.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Empirical processes with applications to statistics

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.820157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.578422Z digest=sha256:7d27284f034d95aec2cbdcf5400d8d0f04f9f12ef879940198be5d8016a3dda5

Observation b583e619-ff3c-41d5-9575-ce097cb918ac · outbound

This paper cites The transportation cost from the uniform measure to the empirical measure in dimension 3.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations The transportation cost from the uniform measure to the empirical measure in dimension 3

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.801385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.582152Z digest=sha256:19ca34195fc3b56ac90827edbff5db55bc529d7dce71d49521c95c23ff71bb57

Observation 47d222b1-4e71-4f7b-9f30-689bea01c4ef · outbound

This paper cites High-Dimensional Probability: An Introduction with Applications in Data Science.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 29

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unresolved
no resolver link, observed 2026-08-14T10:39:53.585726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.585726Z digest=sha256:387f68f7b9029bee2bc5cb561370c879a61f60f9294d4eed43803be0711f8c25

Observation 0c4a23db-ddca-4191-a642-3737df396802 · outbound

This paper cites an unresolved cited work.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Unresolved cited work

Reference 30

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raw_fallback, observed 2026-08-14T10:39:53.784580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.589769Z digest=sha256:6d396c513263b56a32c94e5180da5755590523f05de3f4f64bee13014a62dae3

Observation 312945d6-88ef-4f78-a9d9-3daf0f477c55 · outbound

This paper cites Functional properties of MMSE and mutual information.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Functional properties of MMSE and mutual information

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-14T10:39:53.773303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.593005Z digest=sha256:abc999f35011be49deaa0b90406b0e0d5fc1cbc8cff76607f595aec12ca1853f

Observation abaff8d2-1431-4c83-a70b-c353dd2a2cdf · outbound

This paper cites Optimal estimation of Gaussian mixtures via denoised method of moments.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Optimal estimation of Gaussian mixtures via denoised method of moments

Reference 32

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verified exact
local_arxiv, observed 2026-08-14T10:39:53.648042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.596258Z digest=sha256:82b216fe80e80177a3beb2a582fccaec907dda829aa5316a40fb375badbec24f

Observation 8985ad75-6f5f-48e8-a058-c921631d979c · outbound

This paper cites an unresolved cited work.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Unresolved cited work

Reference 33

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unresolved
raw_fallback, observed 2026-08-14T10:39:53.762008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T10:39:53.599834Z digest=sha256:54e7e0a37ae3cd5c08ae2262a14ce2c56d3105e976e48c7f11747d7d26a41cca

Observation b9691851-2dbf-4b6a-acf4-738644073d4e · outbound

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

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Global analysis of expectation maximization for mixtures of two G aussians

Reference 34

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unresolved
no resolver link, observed 2026-08-14T10:39:53.603098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:39:53.603098Z digest=sha256:ca22da16ea1ee35b7e1ffbdf529bcca1b232b44bfbab6a78de460ac7da79f52d

Observation f84b550f-ac2f-4cee-88a4-005ed1db263c · outbound

This paper cites On convergence properties of the EM algorithm for G aussian mixtures.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations On convergence properties of the EM algorithm for G aussian mixtures

Reference 35

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source=arxiv_source observed=2026-08-14T10:39:53.606445Z digest=sha256:4f0aa8c23e9cbc53fc25395ef23797212a4b10dfa209dd2a84414d4e8d4d3a14

Observation 41956d32-976f-4c53-9605-77cbb4bff0cd · outbound

This paper cites Yang and A.

Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations Yang and A

Reference 36

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raw_fallback, observed 2026-08-14T10:39:53.736779Z

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source=arxiv_source observed=2026-08-14T10:39:53.611050Z digest=sha256:2581a6787968facf70044cd772f8e23f6b884eea20e9727b67376d42cf0447fb

Pith citing papers

Observation 4a29b0fc-cd24-4f5c-81ba-f00b520a34d8 · inbound

On Model-Based Clustering With Entropic Optimal Transport cites this paper.

On Model-Based Clustering With Entropic Optimal Transport Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations

Reference 68

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source=arxiv_source observed=2026-05-07T15:09:29.750492Z digest=sha256:e4aae282cf3adc084adb961ccfcbf77d1b356662b30ecbf5a5b399b81ac5e2f4

Observation ade24c57-94cf-4757-8840-5d45bc5d2f2b · inbound

Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data cites this paper.

Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in $O(\sqrt{n})$ iterations

Reference 56

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source=arxiv_source observed=2026-07-31T03:15:47.958266Z digest=sha256:1577b6900fa2679db86ff9d4da264dc462a0f9f0f9543acfc6dbf2f98f3ea794