Manifold-aligned Neighbor Embedding

2022/05/19 by Mohammad Tariqul Islam, Islam, Mohammad Tariqul, Jason W. Fleischer +1 · 1 citation
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.LG

paper · pdf · doi:10.48550/arxiv.2205.11257

Accepted at the ICLR 2022 Workshop on Geometrical and Topological Representation Learning

arxiv created 2022/05/19 · arxiv updated 2022/05/24

Abstract

In this paper, we introduce a neighbor embedding framework for manifold alignment. We demonstrate the efficacy of the framework using a manifold-aligned version of the uniform manifold approximation and projection algorithm. We show that our algorithm can learn an aligned manifold that is visually competitive to embedding of the whole dataset.

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• Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias

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• Manifold Alignment Determination: finding correspondences across different data views
• Adaptive Locally Linear Embedding
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• Contrastive Neighborhood Alignment
• Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey