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Survey of vector database management systems
There are now over 20 commercial vector database management systems (VDBMSs), all
produced within the past five years. But embedding-based retrieval has been studied for …
produced within the past five years. But embedding-based retrieval has been studied for …
Oblivious key-value stores and amplification for private set intersection
Many recent private set intersection (PSI) protocols encode input sets as polynomials. We
consider the more general notion of an oblivious key-value store (OKVS), which is a data …
consider the more general notion of an oblivious key-value store (OKVS), which is a data …
A survey on learning to hash
Nearest neighbor search is a problem of finding the data points from the database such that
the distances from them to the query point are the smallest. Learning to hash is one of the …
the distances from them to the query point are the smallest. Learning to hash is one of the …
A survey on deep hashing methods
Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …
distances from them to the queries, which is a basic task in a range of fields, including …
Practical and optimal LSH for angular distance
We show the existence of a Locality-Sensitive Hashing (LSH) family for the angular distance
that yields an approximate Near Neighbor Search algorithm with the asymptotically optimal …
that yields an approximate Near Neighbor Search algorithm with the asymptotically optimal …
New directions in nearest neighbor searching with applications to lattice sieving
To solve the approximate nearest neighbor search problem (NNS) on the sphere, we
propose a method using locality-sensitive filters (LSF), with the property that nearby vectors …
propose a method using locality-sensitive filters (LSF), with the property that nearby vectors …
Hashing for similarity search: A survey
Similarity search (nearest neighbor search) is a problem of pursuing the data items whose
distances to a query item are the smallest from a large database. Various methods have …
distances to a query item are the smallest from a large database. Various methods have …
Optimal data-dependent hashing for approximate near neighbors
We show an optimal data-dependent hashing scheme for the approximate near neighbor
problem. For an n-point dataset in a d-dimensional space our data structure achieves query …
problem. For an n-point dataset in a d-dimensional space our data structure achieves query …
[PDF][PDF] Approximate nearest neighbor: Towards removing the curse of dimensionality
S Har-Peled, P Indyk, R Motwani - 2012 - dspace.mit.edu
Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality Page 1
Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality The MIT …
Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality The MIT …
Explaining the success of nearest neighbor methods in prediction
Many modern methods for prediction leverage nearest neighbor search to find past training
examples most similar to a test example, an idea that dates back in text to at least the 11th …
examples most similar to a test example, an idea that dates back in text to at least the 11th …