Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE

Aditya Ravuri; Neil D. Lawrence

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Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE

Aditya Ravuri, Neil D. Lawrence

, 2024.

Abstract

This paper shows that the dimensionality reduction methods, UMAP and t-SNE, can be approximately recast as MAP inference methods corresponding to a generalized Wishart-based model introduced in ProbDR. This interpretation offers deeper theoretical insights into these algorithms, while introducing tools with which similar dimensionality reduction methods can be studied.

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BibTeX


@Misc{towards-one-model-for-classical-dimensionality-reduction,
  title = 	 {Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE},
  author = 	 {Ravuri, Aditya and Lawrence, Neil D.},
  year = 	 {2024},
  url = 	 {/publications/towards-one-model-for-classical-dimensionality-reduction.html},
  abstract = 	 {This paper shows that the dimensionality reduction methods, UMAP and t-SNE, can be approximately recast as MAP inference methods corresponding to a generalized Wishart-based model introduced in ProbDR. This interpretation offers deeper theoretical insights into these algorithms, while introducing tools with which similar dimensionality reduction methods can be studied.
}
}

Endnote

%0 Generic
%T Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
%A Aditya Ravuri
%A Neil D. Lawrence
%D 2024	
%F towards-one-model-for-classical-dimensionality-reduction
%U /publications/towards-one-model-for-classical-dimensionality-reduction.html
%X This paper shows that the dimensionality reduction methods, UMAP and t-SNE, can be approximately recast as MAP inference methods corresponding to a generalized Wishart-based model introduced in ProbDR. This interpretation offers deeper theoretical insights into these algorithms, while introducing tools with which similar dimensionality reduction methods can be studied.

RIS


TY  - GEN
TI  - Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE
AU  - Aditya Ravuri
AU  - Neil D. Lawrence
DA  - 2024/05/27	
ID  - towards-one-model-for-classical-dimensionality-reduction
UR  - /publications/towards-one-model-for-classical-dimensionality-reduction.html
AB  - This paper shows that the dimensionality reduction methods, UMAP and t-SNE, can be approximately recast as MAP inference methods corresponding to a generalized Wishart-based model introduced in ProbDR. This interpretation offers deeper theoretical insights into these algorithms, while introducing tools with which similar dimensionality reduction methods can be studied.

ER  -

APA


Ravuri, A. & Lawrence, N.D.. (2024). Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE.  Available from /publications/towards-one-model-for-classical-dimensionality-reduction.html.