258 citations · 935 across the 92 of their papers we have counts for
7 papers · 1 filter
Revisiting Winner Take All (WTA) Hashing for Sparse Datasets
Beidi Chen, Anshumali Shrivastava
WTA (Winner Take All) hashing has been successfully applied in many large scale vision applications. This hashing scheme was tailored to take advantage of the comparative reasoning…
Sub-Linear Privacy-Preserving Near-Neighbor Search
M. Sadegh Riazi, Beidi Chen, Anshumali Shrivastava +2
In Near-Neighbor Search (NNS), a new client queries a database (held by a server) for the most similar data (near-neighbors) given a certain similarity metric. The Privacy-Preservi…
SSH (Sketch, Shingle, & Hash) for Indexing Massive-Scale Time Series
Chen Luo, Anshumali Shrivastava
Similarity search on time series is a frequent operation in large-scale data-driven applications. Sophisticated similarity measures are standard for time series matching, as they a…
Near-Isometric Binary Hashing for Large-scale Datasets
Amirali Aghazadeh, Andrew Lan, Anshumali Shrivastava +1
We develop a scalable algorithm to learn binary hash codes for indexing large-scale datasets. Near-isometric binary hashing (NIBH) is a data-dependent hashing scheme that quantizes…
Exact Weighted Minwise Hashing in Constant Time
Anshumali Shrivastava
Weighted minwise hashing (WMH) is one of the fundamental subroutine, required by many celebrated approximation algorithms, commonly adopted in industrial practice for large scale-s…
2-Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search
Ping Li, Michael Mitzenmacher, Anshumali Shrivastava
The method of random projections has become a standard tool for machine learning, data mining, and search with massive data at Web scale. The effective use of random projections re…