Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Locality-sensitive hashing

Known as: LSH, Locality Sensitive Hashing 
Locality-sensitive hashing (LSH) reduces the dimensionality of high-dimensional data. LSH hashes input items so that similar items map to the same… Expand
Wikipedia

Related topics

Related topics

33 relations
Andrei BroderAnti-spam techniquesApproximate string matchingBag-of-words model in computer vision
Expand

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2014
Highly Cited
2014
Beyond Locality-Sensitive Hashing
We present a new data structure for the c-approximate near neighbor problem (ANN) in the Euclidean space. For n points in Rd, our… Expand
Highly Cited
2012
Highly Cited
2012
Super-Bit Locality-Sensitive Hashing
Sign-random-projection locality-sensitive hashing (SRP-LSH) is a probabilistic dimension reduction method which provides an… Expand
  • figure 1
  • figure 2
  • figure 3
Highly Cited
2011
Highly Cited
2011
Fast locality-sensitive hashing
Locality-sensitive hashing (LSH) is a basic primitive in several large-scale data processing applications, including nearest… Expand
  • figure 1
  • figure 2
  • figure 3
Highly Cited
2010
Highly Cited
2010
Non-Metric Locality-Sensitive Hashing
Non-metric distances are often more reasonable compared with metric ones in terms of consistency with human perceptions. However… Expand
  • figure 1
  • figure 2
  • table 1
  • figure 3
  • table 2
Highly Cited
2010
Highly Cited
2010
Locality sensitive hashing: A comparison of hash function types and querying mechanisms
It is well known that high-dimensional nearest neighbor retrieval is very expensive. Dramatic performance gains are obtained… Expand
  • figure 1
  • figure 3
  • figure 2
  • figure 4
  • table 1
Highly Cited
2009
Highly Cited
2009
Kernelized locality-sensitive hashing for scalable image search
  • B. Kulis, K. Grauman
  • IEEE 12th International Conference on Computer…
  • 2009
    • Corpus ID: 7201154
Fast retrieval methods are critical for large-scale and data-driven vision applications. Recent work has explored ways to embed… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Highly Cited
2009
Highly Cited
2009
Semantic hashing
We show how to learn a deep graphical model of the word-count vectors obtained from a large set of documents. The values of the… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2008
Highly Cited
2008
Locality-Sensitive Hashing for Finding Nearest Neighbors [Lecture Notes]
This lecture note describes a technique known as locality-sensitive hashing (LSH) that allows one to quickly find similar entries… Expand
Highly Cited
2004
Highly Cited
2004
Locality-sensitive hashing scheme based on p-stable distributions
We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under lp norm, based on p… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2003
Highly Cited
2003
Fast pose estimation with parameter-sensitive hashing
Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality… Expand
  • figure 1
  • figure 3
  • table 1
  • figure 4
  • figure 5
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License
ACCEPT & CONTINUE