On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings

Research article (arXiv (Cornell University), 2020) · cited 48× · AI/ML
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On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings

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On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings. Retrieved May 24, 2026, from https://4ort.xyz/entity/on-the-choice-of-the-low-dimensional-domain-for-high-dimensional-bayesian-optimization-using-random-embeddings
MLA “On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/on-the-choice-of-the-low-dimensional-domain-for-high-dimensional-bayesian-optimization-using-random-embeddings.
BibTeX @misc{4ortxyz_on-the-choice-of-the-low-dimensional-domain-for-high-dimensional-bayesian-optimization-using-random-embeddings_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{On the choice of the low-dimensional domain for high-dimensional bayesian optimization using random embeddings}}, year = {2026}, url = {https://4ort.xyz/entity/on-the-choice-of-the-low-dimensional-domain-for-high-dimensional-bayesian-optimization-using-random-embeddings}, note = {Accessed: 2026-05-24}}
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