Unsupervised Space Partitioning for Nearest Neighbor Search. (arXiv:2206.08091v1 [cs.LG])

Web: http://arxiv.org/abs/2206.08091

Approximate Nearest Neighbor Search (ANNS) in high dimensional spaces is
crucial for many real-life applications (e.g., e-commerce, web, multimedia,
etc.) dealing with an abundance of data. In this paper, we propose an
end-to-end learning framework that couples the partitioning (one key step of
ANNS) and learning-to-search steps using a custom loss function. A key
advantage of our proposed solution is that it does not require any expensive
pre-processing of the dataset, which is one of the key limitations of the …

arxiv lg partitioning search space unsupervised