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» Fast Nearest Neighbor Search in High-Dimensional Space
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77
Voted
ICML
1994
IEEE
15 years 29 days ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
VLDB
2007
ACM
169views Database» more  VLDB 2007»
15 years 9 months ago
Peer-to-Peer Similarity Search in Metric Spaces
This paper addresses the efficient processing of similarity queries in metric spaces, where data is horizontally distributed across a P2P network. The proposed approach does not r...
Christos Doulkeridis, Akrivi Vlachou, Yannis Kotid...
EDBT
2009
ACM
184views Database» more  EDBT 2009»
15 years 4 months ago
Distributed similarity search in high dimensions using locality sensitive hashing
In this paper we consider distributed K-Nearest Neighbor (KNN) search and range query processing in high dimensional data. Our approach is based on Locality Sensitive Hashing (LSH...
Parisa Haghani, Sebastian Michel, Karl Aberer
72
Voted
DAGM
2007
Springer
15 years 3 months ago
A Fast and Reliable Coin Recognition System
This paper presents a reliable coin recognition system that is based on a registration approach. To optimally align two coins we search for a rotation in order to reach a maximal n...
Marco Reisert, Olaf Ronneberger, Hans Burkhardt
91
Voted
ICML
2004
IEEE
15 years 2 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul