We study the Approximate Nearest Neighbor problem for metric spaces where the query points are constrained to lie on a subspace of low doubling dimension.
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
Computing the similarity between objects is a central task for many applications in the field of inf...
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
Given a set of n points in d-dimensional Euclidean space, S ae E d , and a query point q 2 E d ,...
AbstractThe nearest neighbor search (NNS) problem is the following: Given a set of n points P={p1, …...
Given a set of n points in d-dimensional Euclidean space, S ⊂ E d, and a query point q ∈ E d, we wis...
We study the Partial Nearest Neighbor Problem that consists in pre-processing n points D from d-dime...
Given a set of points in a metric space, a fundamental problem is to preprocess these points for ans...
Consider a set S of n data points in real d-dimensional space, R d , where distances are measured ...
Consider a set S of n data points in real d-dimensional space, R-d, where distances are measured usi...
In order to improve efficiency in Approximate Near-est Neighbor (ANN) search, we exploit the structu...
The nearest neighbor problem is the following: Given a set of n points P = fp1�:::�p ng in some metr...
Existing models for nearest neighbor search in multidimensional spaces are not appropriate for query...
Most research on nearest neighbor algorithms in the literature has been focused on the Euclidean cas...
Let k be a nonnegative integer. In the approximate k-flat nearest neighbor (k-ANN) problem, we are g...
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
Computing the similarity between objects is a central task for many applications in the field of inf...
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
Given a set of n points in d-dimensional Euclidean space, S ae E d , and a query point q 2 E d ,...
AbstractThe nearest neighbor search (NNS) problem is the following: Given a set of n points P={p1, …...
Given a set of n points in d-dimensional Euclidean space, S ⊂ E d, and a query point q ∈ E d, we wis...
We study the Partial Nearest Neighbor Problem that consists in pre-processing n points D from d-dime...
Given a set of points in a metric space, a fundamental problem is to preprocess these points for ans...
Consider a set S of n data points in real d-dimensional space, R d , where distances are measured ...
Consider a set S of n data points in real d-dimensional space, R-d, where distances are measured usi...
In order to improve efficiency in Approximate Near-est Neighbor (ANN) search, we exploit the structu...
The nearest neighbor problem is the following: Given a set of n points P = fp1�:::�p ng in some metr...
Existing models for nearest neighbor search in multidimensional spaces are not appropriate for query...
Most research on nearest neighbor algorithms in the literature has been focused on the Euclidean cas...
Let k be a nonnegative integer. In the approximate k-flat nearest neighbor (k-ANN) problem, we are g...
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
Computing the similarity between objects is a central task for many applications in the field of inf...
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is ...
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