Accelerating t-SNE using a uniform grid-based approximation

Bachelor Thesis (2024)
Author(s)

M.F. Otten (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

M. Skrodzki – Mentor (TU Delft - Computer Graphics and Visualisation)

Elmar Eisemann – Mentor (TU Delft - Computer Graphics and Visualisation)

M.A. Migut – Graduation committee member (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
26-06-2024
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Dimensionality reduction is an important task in high-dimensional data visualisation. Among the popular algorithms for achieving this is t-SNE, which aims to preserve local neighbourhoods in the lower-dimensional embeddings. While t-SNE traditionally works in Euclidean space, embedding in hyperbolic space offers several advantages, specifically for data of arbitrary size and exponential growth, such as tree-based structures. We propose a new solution to approximate and accelerate the calculation of t-SNE gradients using a uniform grid structure. This new method produces embeddings with better neighbourhood preservation than previous solutions, while also providing better runtime performance.

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