ArticleJournal of machine learning research : JMLR
On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models.
Article in Journal of machine learning research : JMLR. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- ebnm: An R Package for Solving the Empirical Bayes Normal Means Problem Using a Variety of Prior Families.Journal of statistical software · 2025Article
- Score-Based Diffusion Modeling for Nonparametric Empirical Bayes in Heteroscedastic Gaussian Mixtures.Advances in neural information processing systems · 2025Article
- On Efficient and Scalable Computation of the Nonparametric Maximum Likelihood Estimator in Mixture Models.Journal of machine learning research : JMLRArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
In this paper, we focus on the computation of the nonparametric maximum likelihood estimator (NPMLE) in multivariate mixture models. Our approach discretizes this infinite dimensional convex optimization problem by setting fixed support points for the NPMLE and optimizing over the mixing proportions. We propose an efficient and scalable semismooth Newton based augmented Lagrangian method (ALM). Our algorithm outperforms the state-of-the-art methods (Kim et al., 2020; Koenker and Gu, 2017), capable of handling
Indexed as
Identifiers
41815789PMC12975118What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.