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Dirichlet process mixture models made scalable and effective by means of massive distribution

Research article (Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2019) · cited 12× · AI/ML
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Dirichlet process mixture models made scalable and effective by means of massive distribution

Summary

Dirichlet process mixture models made scalable and effective by means of massive distribution is a scholarly article[1].

Key Facts

  • Dirichlet process mixture models made scalable and effective by means of massive distribution's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Dirichlet process mixture models made scalable and effective by means of massive distribution. Retrieved May 24, 2026, from https://4ort.xyz/entity/dirichlet-process-mixture-models-made-scalable-and-effective-by-means-of-massive-distribution
MLA “Dirichlet process mixture models made scalable and effective by means of massive distribution.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dirichlet-process-mixture-models-made-scalable-and-effective-by-means-of-massive-distribution.
BibTeX @misc{4ortxyz_dirichlet-process-mixture-models-made-scalable-and-effective-by-means-of-massive-distribution_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Dirichlet process mixture models made scalable and effective by means of massive distribution}}, year = {2026}, url = {https://4ort.xyz/entity/dirichlet-process-mixture-models-made-scalable-and-effective-by-means-of-massive-distribution}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Dirichlet process mixture models made scalable and effective by means of massive distribution — https://4ort.xyz/entity/dirichlet-process-mixture-models-made-scalable-and-effective-by-means-of-massive-distribution (retrieved 2026-05-24)

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