The Excellence
Directory Platform Template

Paper by Tepper et al. proposing GleanVec, a method to accelerate vector search using minimalist nonlinear dimensionality reduction. Improves efficiency for high-dimensional vector queries.

Research paper introducing LeanVec, a technique to accelerate vector search by reducing vector dimensionality while preserving search accuracy. Published as an arXiv preprint in 2023 by Mariano Tepper et al.

Pairwise Controlled Manifold Approximation - a dimensionality reduction technique that preserves both local and global structure better than UMAP or t-SNE. Particularly effective for visualizing complex embedding spaces.

Uniform Manifold Approximation and Projection - a dimensionality reduction technique used for visualizing high-dimensional vector embeddings and compressing vectors while preserving structure. Popular for embedding analysis and visualization.

Uniform Manifold Approximation and Projection - a non-linear dimensionality reduction technique that preserves both local and global data structure. More scalable than t-SNE while maintaining superior visualization quality and cluster separation for high-dimensional embeddings.