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DEXA
2006
Springer
190views Database» more  DEXA 2006»
13 years 9 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
FOCS
2006
IEEE
13 years 11 months ago
On the Optimality of the Dimensionality Reduction Method
We investigate the optimality of (1+ )-approximation algorithms obtained via the dimensionality reduction method. We show that: • Any data structure for the (1 + )-approximate n...
Alexandr Andoni, Piotr Indyk, Mihai Patrascu
ICIP
2008
IEEE
14 years 7 months ago
On the estimation of geodesic paths on sampled manifolds under random projections
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
Mona Mahmoudi, Pierre Vandergheynst, Matteo Sorci
DEXAW
1999
IEEE
168views Database» more  DEXAW 1999»
13 years 10 months ago
Using the Distance Distribution for Approximate Similarity Queries in High-Dimensional Metric Spaces
We investigate the problem of approximate similarity (nearest neighbor) search in high-dimensional metric spaces, and describe how the distance distribution of the query object ca...
Paolo Ciaccia, Marco Patella
ICCV
2007
IEEE
14 years 7 months ago
High-Dimensional Feature Matching: Employing the Concept of Meaningful Nearest Neighbors
Matching of high-dimensional features using nearest neighbors search is an important part of image matching methods which are based on local invariant features. In this work we hi...
Dusan Omercevic, Ondrej Drbohlav, Ales Leonardis