Multidimensional Projection
Multidimensional projection (MP) techniques aim to visualize high-dimensional data in lower dimensions (typically 2D or 3D) while preserving essential data relationships. Current research focuses on improving projection quality through tailored metrics reflecting user preferences, developing efficient algorithms like approximate UMAP for real-time applications, and addressing challenges like distortion and bias in existing methods such as t-SNE and UMAP. These advancements are crucial for enhancing data exploration, interpretation, and decision-making across diverse fields, from robotics and machine learning to bioinformatics and data visualization.
Papers
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