We investigate exact indexing for high dimensional lp norms based on the 1-Lipschitz property and projection operators. The orthogonal projection that satisfies the 1-Lipschitz property for the lp norm is described. The adaptive projection defined by the first principal component is introduced
In this thesis, we study high dimensional approximate similarity search algorithms. High dimensional...
We study exact and approximate methods for maximum inner product search, a fundamental problem in a ...
[[abstract]]The method of projections onto convex sets (POCS) is a technique for restoring signals f...
We investigate exact indexing for high dimensional lp norms based on the 1-Lipschitz property and pr...
AbstractThe work of de Boor and Fix on spline approximation by quasiinterpolants has had far-reachin...
AbstractDegrading performance of indexing schemes for exact similarity search in high dimensions has...
SIGLEAvailable from British Library Document Supply Centre-DSC:9106.170(316) / BLDSC - British Libra...
We develop dynamic dimensionality reduction based on the approximation of the standard inner-product...
AbstractWe estimate the Lp(Rd)-approximation rate (1≤p≤∞) provided dilates of an orthogonal projecti...
AbstractFor a given nonatomic finite measure space (X, μ), best approximations of elements of Lp(X, ...
[[abstract]]The method of projections onto convex sets (POCS) is a technique for restoring signals f...
Abstract—We address the problem of domain adaptation for binary classification which arises when the...
AbstractBest approximation in C(X) by elements of a Chebyshev subspace is governed by Haar's theorem...
Many problems in information processing involve some form of dimensionality reduction. In this paper...
A method is introduced to learn and represent similarity with lin-ear operators in kernel induced Hi...
In this thesis, we study high dimensional approximate similarity search algorithms. High dimensional...
We study exact and approximate methods for maximum inner product search, a fundamental problem in a ...
[[abstract]]The method of projections onto convex sets (POCS) is a technique for restoring signals f...
We investigate exact indexing for high dimensional lp norms based on the 1-Lipschitz property and pr...
AbstractThe work of de Boor and Fix on spline approximation by quasiinterpolants has had far-reachin...
AbstractDegrading performance of indexing schemes for exact similarity search in high dimensions has...
SIGLEAvailable from British Library Document Supply Centre-DSC:9106.170(316) / BLDSC - British Libra...
We develop dynamic dimensionality reduction based on the approximation of the standard inner-product...
AbstractWe estimate the Lp(Rd)-approximation rate (1≤p≤∞) provided dilates of an orthogonal projecti...
AbstractFor a given nonatomic finite measure space (X, μ), best approximations of elements of Lp(X, ...
[[abstract]]The method of projections onto convex sets (POCS) is a technique for restoring signals f...
Abstract—We address the problem of domain adaptation for binary classification which arises when the...
AbstractBest approximation in C(X) by elements of a Chebyshev subspace is governed by Haar's theorem...
Many problems in information processing involve some form of dimensionality reduction. In this paper...
A method is introduced to learn and represent similarity with lin-ear operators in kernel induced Hi...
In this thesis, we study high dimensional approximate similarity search algorithms. High dimensional...
We study exact and approximate methods for maximum inner product search, a fundamental problem in a ...
[[abstract]]The method of projections onto convex sets (POCS) is a technique for restoring signals f...
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