Paper Citation Record · LEDGER

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

As of 8 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 6 inbound Pith citation observations for arXiv:2509.07355.

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

pith.paper-citation-record.v1
2509.07355 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

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measured 59 of 59 standing notices

One-hop event checks from named stored sources.

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measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:03:06.816797Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T22:05:05.575141Z

Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation 83fe7982-99cc-4a2e-b1de-1bc0f82f7904 · outbound

This paper cites A unified maximum likelihood approach for estimating symmetric properties of discrete distributions.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation A unified maximum likelihood approach for estimating symmetric properties of discrete distributions

Reference 1

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Observation a2b718d2-87b8-4cbb-9158-4b84cd3f25c3 · outbound

This paper cites Optimal probability estimation with applications to prediction and classification.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Optimal probability estimation with applications to prediction and classification

Reference 2

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Observation 9df7b3d1-045f-46c5-9529-8559288766ab · outbound

This paper cites Chen and Joshua Goodman.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Chen and Joshua Goodman

Reference 3

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Observation 9b3a4bf0-2d51-46dd-b177-251a7d7c4e9d · outbound

This paper cites Elements of Information Theory.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Elements of Information Theory

Reference 4

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This paper cites Two modeling strategies for empirical B ayes estimation.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Two modeling strategies for empirical B ayes estimation

Reference 5

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Unresolved cited work

Reference 6

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Observation 68e1a36a-21a6-48f7-a7f8-016cfbeedc17 · outbound

This paper cites Theory of optimal experiments.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Theory of optimal experiments

Reference 7

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This paper cites Towards competitive n-gram smoothing.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Towards competitive n-gram smoothing

Reference 8

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This paper cites An algorithm for quadratic programming.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation An algorithm for quadratic programming

Reference 9

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Unresolved cited work

Reference 10

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Observation f9b06804-ae4b-47ab-adde-9da273a661e4 · outbound

This paper cites Asymptotic efficiency of simple decisions for the compound decision problem.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Asymptotic efficiency of simple decisions for the compound decision problem

Reference 11

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Unresolved cited work

Reference 12

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Observation 3289f5f4-142d-475d-9c3e-6fa4c3baff92 · outbound

This paper cites Gale and Geoffrey Sampson.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Gale and Geoffrey Sampson

Reference 13

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Observation f618b8af-9d33-4270-bcd3-64a859d56a9f · outbound

This paper cites Approximate independence of permutation mixtures.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Approximate independence of permutation mixtures

Reference 14

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Observation bdee77eb-75f6-4944-8b9e-3d14c1ada9ae · outbound

This paper cites The broad optimality of profile maximum likelihood.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation The broad optimality of profile maximum likelihood

Reference 15

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Observation ebc39f9a-fdea-4420-a030-8ee4fbbc78e2 · outbound

This paper cites Asymptotic solutions of the compound decision problem for two completely specified distributions.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Asymptotic solutions of the compound decision problem for two completely specified distributions

Reference 16

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Observation fd788aa5-fcc3-4b8c-8e7e-c882b3652fb3 · outbound

This paper cites On the competitive analysis and high accuracy optimality of profile maximum likelihood.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation On the competitive analysis and high accuracy optimality of profile maximum likelihood

Reference 17

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Observation 17004dea-8a78-4833-863c-a21c89df64de · outbound

This paper cites Revisiting F rank- W olfe: Projection-free sparse convex optimization.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Revisiting F rank- W olfe: Projection-free sparse convex optimization

Reference 18

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Observation 87c8649e-6d62-42f3-a176-54bb1f99ce7a · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Unresolved cited work

Reference 19

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Observation 06cb1836-877b-4122-b464-ec90de526030 · outbound

This paper cites Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods

Reference 20

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Observation 10a4a043-2a63-4ac0-9876-983b134a2591 · outbound

This paper cites Minimax estimation of functionals of discrete distributions.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Minimax estimation of functionals of discrete distributions

Reference 21

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Observation ac790e47-f0a7-4b2c-8f19-9da0911c117f · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation On information and sufficiency

Reference 22

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This paper cites Convex optimization, shape constraints, compound decisions, and empirical B ayes rules.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Convex optimization, shape constraints, compound decisions, and empirical B ayes rules

Reference 23

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation The performance of universal encoding

Reference 24

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Observation e8e5ef81-ed6c-4651-96e2-ce209b5a70bc · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Kiefer and J

Reference 25

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This paper cites Estimating T -cell repertoire diversity: limitations of classical estimators and a new approach.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Estimating T -cell repertoire diversity: limitations of classical estimators and a new approach

Reference 26

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation The geometry of mixture likelihoods: a general theory

Reference 27

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Observation 4c558b3e-4058-4222-8dcc-520119c0aa53 · outbound

This paper cites Mixture models: Theory, geometry and applications.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Mixture models: Theory, geometry and applications

Reference 28

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This paper cites A fast, lock-free approach for efficient parallel counting of occurrences of k-mers.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation A fast, lock-free approach for efficient parallel counting of occurrences of k-mers

Reference 29

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation McAllester and Robert E

Reference 30

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Probability and computing

Reference 31

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Observation 57e393fc-a210-46e6-a2fc-f34fed0b174c · outbound

This paper cites Large-scale Multiple Testing: Fundamental Limits of False Discovery Rate Control and Compound Oracle.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Large-scale Multiple Testing: Fundamental Limits of False Discovery Rate Control and Compound Oracle

Reference 32

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This paper cites Competitive distribution estimation: Why is G ood- T uring good.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Competitive distribution estimation: Why is G ood- T uring good

Reference 33

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation On modeling profiles instead of values

Reference 34

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Observation 85f722e3-8c00-4729-ae6d-8b74eee4c141 · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Santhanam, and Junan Zhang

Reference 35

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Observation 851f18b9-4328-4aa6-ab9d-ca6a01e96aa9 · outbound

This paper cites Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models

Reference 36

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Observation 1a5b2fb3-3e12-4c55-98e0-c3decc91f5ea · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Information theory: From coding to learning

Reference 37

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Asymptotically subminimax solutions of compound statistical decision problems

Reference 38

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation An empirical B ayes approach to statistics

Reference 39

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Maximum likelihood estimation of a compound P oisson process

Reference 40

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation A statistical interpretation of term specificity and its application in retrieval

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:31:25.178443Z

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Observation e2fad22c-4bb5-48e6-aec4-c4be99caa881 · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation A survey of modern authorship attribution methods

Reference 42

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Observation 3be2fbb9-8b35-4c6b-a5f8-746654d36b40 · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Empirical Bayes estimation: When does $g$-modeling beat $f$-modeling in theory (and in practice)?

Reference 43

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Unresolved cited work

Reference 44

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Observation 2c9c0ac4-80b4-4ff9-ac7b-9a74d0c735a7 · outbound

This paper cites Capacity of noisy permutation channels.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Capacity of noisy permutation channels

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:31:25.144533Z

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Observation 3ae0c01b-0978-4dc3-b3f0-5750b290c674 · outbound

This paper cites Census Bureau.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Census Bureau

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:31:25.133314Z

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Observation 95105337-3f46-46d0-9957-7b33f3c539d9 · outbound

This paper cites Census Bureau.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Census Bureau

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:31:25.122950Z

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Observation c5f5b4a4-4eee-4401-8287-7f7bb3095a2f · outbound

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Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation The complexity of computing the permanent

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:31:25.111767Z

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Observation 8789d520-de9c-4470-9283-90d83e85218b · outbound

This paper cites On the Minimum Attainable Risk in Permutation Invariant Problems.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation On the Minimum Attainable Risk in Permutation Invariant Problems

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-04T22:31:24.996112Z

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Observation 7cbb2dd5-67b8-46e6-b51f-f3a0c9de8263 · outbound

This paper cites Minimax rates of entropy estimation on large alphabets via best polynomial approximation.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Minimax rates of entropy estimation on large alphabets via best polynomial approximation

Reference 50

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Observation e263103b-117f-4cf6-af68-718a6f298e9d · outbound

This paper cites Chebyshev polynomials, moment matching, and optimal estimation of the unseen.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Chebyshev polynomials, moment matching, and optimal estimation of the unseen

Reference 51

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This paper cites The sequential generation of d -optimum experimental designs.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation The sequential generation of d -optimum experimental designs

Reference 52

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Observation cdc24388-cb35-4d30-a9ae-652f8af5fdeb · outbound

This paper cites Compound decision theory and empirical B ayes methods.

Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation Compound decision theory and empirical B ayes methods

Reference 53

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Pith citing papers

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Universal priors: solving empirical Bayes via Bayesian inference and pretraining cites this paper.

Universal priors: solving empirical Bayes via Bayesian inference and pretraining Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 8

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Observation 270b4646-df0d-4f84-9b47-3e7c2ed4d24c · inbound

Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures cites this paper.

Adaptivity of the NPMLE to finitely discrete mixing distributions in Gaussian/Poisson mixtures Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 2

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Poisson Empirical Bayes via Gamma-Smoothed Nonparametric Maximum Likelihood cites this paper.

Poisson Empirical Bayes via Gamma-Smoothed Nonparametric Maximum Likelihood Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 23

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Observation 6fa97f3a-ca08-47b7-970f-7757d54e759d · inbound

NOVA: Fundamental Limits of Knowledge Discovery Through AI cites this paper.

NOVA: Fundamental Limits of Knowledge Discovery Through AI Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 5

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Observation 765d6c31-a796-448f-b513-7edd9ca09de7 · inbound

NOVA: Fundamental Limits of Knowledge Discovery Through AI cites this paper.

NOVA: Fundamental Limits of Knowledge Discovery Through AI Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:05.576942Z

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Observation fd64a0c0-f47d-4011-93b2-b2a720d77ced · inbound

Elementary Symmetric Polynomial Inequalities for Centered Vectors and Matrices cites this paper.

Elementary Symmetric Polynomial Inequalities for Centered Vectors and Matrices Besting Good--Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation

Reference 80

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