5 citations · 19 across the 17 of their papers we have counts for
4 papers · 1 filter
Practical Near Neighbor Search via Group Testing
Joshua Engels, Benjamin Coleman, Anshumali Shrivastava
We present a new algorithm for the approximate near neighbor problem that combines classical ideas from group testing with locality-sensitive hashing (LSH). We reduce the near neig…
Efficient Inference via Universal LSH Kernel
Zichang Liu, Benjamin Coleman, Anshumali Shrivastava
Large machine learning models achieve unprecedented performance on various tasks and have evolved as the go-to technique. However, deploying these compute and memory hungry models…
Graph Reordering for Cache-Efficient Near Neighbor Search
Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava +1
Graph search is one of the most successful algorithmic trends in near neighbor search. Several of the most popular and empirically successful algorithms are, at their core, a simpl…
Density Sketches for Sampling and Estimation
Aditya Desai, Benjamin Coleman, Anshumali Shrivastava
We introduce Density sketches (DS): a succinct online summary of the data distribution. DS can accurately estimate point wise probability density. Interestingly, DS also provides a…