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EDBT
2009
ACM
184views Database» more  EDBT 2009»
14 years 3 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
VLSID
2006
IEEE
183views VLSI» more  VLSID 2006»
14 years 3 months ago
Design Challenges for High Performance Nano-Technology
This tutorial present the key aspects of design challenges and its solutions that are being experienced in VLSI design in the era of nano technology. The focus will be on design c...
Goutam Debnath, Paul J. Thadikaran
ANCS
2005
ACM
14 years 2 months ago
Segmented hash: an efficient hash table implementation for high performance networking subsystems
Hash tables provide efficient table implementations, achieving O(1), query, insert and delete operations at low loads. However, at moderate or high loads collisions are quite freq...
Sailesh Kumar, Patrick Crowley
BMCBI
2010
160views more  BMCBI 2010»
13 years 9 months ago
Extracting consistent knowledge from highly inconsistent cancer gene data sources
Background: Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diver...
Xue Gong, Ruihong Wu, Yuannv Zhang, Wenyuan Zhao, ...
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 9 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger