announcing scann: efficient vector similarity search
ruiqi guo, philip sun, erik lindgren, quan geng, david simcha, felix chern, & sanjiv kumar @ google research
scann is a method for efficient vector similarity search at scale. them implements includes search space pruning & quantization for maximum inner product search & also supports other distance functions such as euclidean distance
the implementation is designed for x86 processors with avx2 support
scann achieves sota performance on ann-benchmarks.com as shown on the
blog post: https://ai.googleblog.com/2020/07/announcing-scann-efficient-vector.html
paper: https://arxiv.org/abs/1908.10396
github: https://github.com/google-research/google-research/tree/master/scann
#icml2020 #similarity #scann #annoy
ruiqi guo, philip sun, erik lindgren, quan geng, david simcha, felix chern, & sanjiv kumar @ google research
scann is a method for efficient vector similarity search at scale. them implements includes search space pruning & quantization for maximum inner product search & also supports other distance functions such as euclidean distance
the implementation is designed for x86 processors with avx2 support
scann achieves sota performance on ann-benchmarks.com as shown on the
glove-100-angular dataset on the attachedblog post: https://ai.googleblog.com/2020/07/announcing-scann-efficient-vector.html
paper: https://arxiv.org/abs/1908.10396
github: https://github.com/google-research/google-research/tree/master/scann
#icml2020 #similarity #scann #annoy