SNE Algorithm

t-distributed Stochastic Neighbor Embedding (t-SNE) is a dimensionality reduction technique used to visualize high-dimensional data in two or three dimensions, preserving local neighborhood structures. Current research focuses on improving t-SNE's robustness to noise, handling temporal data and data streams, and optimizing its computational efficiency through parallelization and novel algorithms like kernelized t-SNE and variations incorporating class probabilities or contrastive learning. These advancements enhance t-SNE's applicability across diverse fields, from single-cell genomics and image analysis to network security and fault detection, providing powerful tools for exploratory data analysis and visualization.