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» Approximate nearest neighbors using sparse representations
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CVPR
2010
IEEE
15 years 5 months ago
SPEC Hashing: Similarity Preserving algorithm for Entropy-based Coding
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
Ruei-Sung Lin, David Ross, Jay Yagnik
CVPR
2005
IEEE
15 years 11 months ago
Efficient Image Matching with Distributions of Local Invariant Features
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
Kristen Grauman, Trevor Darrell
109
Voted
STOC
2002
ACM
177views Algorithms» more  STOC 2002»
15 years 10 months ago
Similarity estimation techniques from rounding algorithms
A locality sensitive hashing scheme is a distribution on a family F of hash functions operating on a collection of objects, such that for two objects x, y, PrhF [h(x) = h(y)] = si...
Moses Charikar
CISS
2008
IEEE
15 years 4 months ago
On sparse representations of linear operators and the approximation of matrix products
—Thus far, sparse representations have been exploited largely in the context of robustly estimating functions in a noisy environment from a few measurements. In this context, the...
Mohamed-Ali Belabbas, Patrick J. Wolfe
DEXA
2006
Springer
190views Database» more  DEXA 2006»
15 years 1 months ago
High-Dimensional Similarity Search Using Data-Sensitive Space Partitioning
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
Sachin Kulkarni, Ratko Orlandic