DEXA
2006
Springer
13 years 8 months ago
2006
Springer
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 ...
ICALP
1992
Springer
13 years 9 months ago
1992
Springer
The "nearest neighbor" relation, or more generally the "k nearest neighbors" relation, defined for a set of points in a metric space, has found many uses in co...
WAIM
2009
Springer
13 years 9 months ago
2009
Springer
In the k-nearest neighbor (KNN) classifier, nearest neighbors involve only labeled data. That makes it inappropriate for the data set that includes very few labeled data. In this ...
SIGMOD
2010
ACM
13 years 9 months ago
2010
ACM
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
ECCV
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. PatchMatch is a fast algorithm for computing dense approximate nearest neighbor correspondences between patches of two image regions [1]. This paper generalizes PatchMatc...
PKDD
2005
Springer
13 years 10 months ago
2005
Springer
Locally Linear Embedding (LLE) has recently been proposed as a method for dimensional reduction of high-dimensional nonlinear data sets. In LLE each data point is reconstructed fro...
ICDE
2006
IEEE
13 years 11 months ago
2006
IEEE
Organizing digital images into semantic categories is imperative for effective browsing and retrieval. In large image collections, an efficient algorithm is crucial to quickly cat...
ADBIS
2007
Springer
13 years 11 months ago
2007
Springer
The M-tree and its variants have been proved to provide an efficient similarity search in database environments. In order to further improve their performance, in this paper we pro...
CVPR
2010
IEEE
14 years 28 days ago
2010
IEEE
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...
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