${\mathbb{R}}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval

Zihao Wang, Hang Yin, Lihui Liu +4

This paper studies the Minimal Embeddable Dimension (MED): the least dimension in which there exists a configuration of $m$ object vectors so that every subset of size at most $k$…