Multiscale Quantization for Fast Similarity Search

NeurIPS 2017 Xiang WuRuiqi GuoAnanda Theertha SureshSanjiv KumarDaniel N. Holtmann-RiceDavid SimchaFelix Yu

We propose a multiscale quantization approach for fast similarity search on large, high-dimensional datasets. The key insight of the approach is that quantization methods, in particular product quantization, perform poorly when there is large variance in the norms of the data points... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.