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» Approximation algorithms for projective clustering
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ICDT
2009
ACM
148views Database» more  ICDT 2009»
15 years 11 months ago
Tight results for clustering and summarizing data streams
In this paper we investigate algorithms and lower bounds for summarization problems over a single pass data stream. In particular we focus on histogram construction and K-center c...
Sudipto Guha
WWW
2010
ACM
15 years 6 months ago
Web-scale k-means clustering
We present two modifications to the popular k-means clustering algorithm to address the extreme requirements for latency, scalability, and sparsity encountered in user-facing web...
D. Sculley
FOCM
2007
55views more  FOCM 2007»
14 years 11 months ago
On Location and Approximation of Clusters of Zeros: Case of Embedding Dimension One
Isolated multiple zeros or clusters of zeros of analytic maps with several variables are known to be difficult to locate and approximate. This article is in the vein of the α-theo...
Marc Giusti, Grégoire Lecerf, Bruno Salvy, ...
KES
2005
Springer
15 years 4 months ago
Towards Adaptive Clustering in Self-monitoring Multi-agent Networks
A Decentralised Adaptive Clustering (DAC) algorithm for self-monitoring impact sensing networks is presented within the context of CSIRO-NASA Ageless Aerospace Vehicle project. DAC...
Piraveenan Mahendra rajah, Mikhail Prokopenko, Pet...
CORR
2008
Springer
77views Education» more  CORR 2008»
14 years 11 months ago
Optimal hash functions for approximate closest pairs on the n-cube
One way to find closest pairs in large datasets is to use hash functions [6], [12]. In recent years locality-sensitive hash functions for various metrics have been given: projecti...
Daniel M. Gordon, Victor Miller, Peter Ostapenko