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» Adaptive K-Means Clustering
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CEC
2005
IEEE
15 years 3 months ago
Multiobjective clustering around medoids
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Julia Handl, Joshua D. Knowles
CPM
2000
Springer
160views Combinatorics» more  CPM 2000»
15 years 2 months ago
Approximation Algorithms for Hamming Clustering Problems
We study Hamming versions of two classical clustering problems. The Hamming radius p-clustering problem (HRC) for a set S of k binary strings, each of length n, is to find p bina...
Leszek Gasieniec, Jesper Jansson, Andrzej Lingas
AINA
2004
IEEE
15 years 1 months ago
An Efficient Clustered Architecture for P2P Networks
Peer-to-peer (P2P) computing offers many attractive features, such as self-organization, load-balancing, availability, fault tolerance, and anonymity. However, it also faces some ...
Juan Li, Son T. Vuong
BMCBI
2007
207views more  BMCBI 2007»
14 years 9 months ago
Analyzing in situ gene expression in the mouse brain with image registration, feature extraction and block clustering
Background: Many important high throughput projects use in situ hybridization and may require the analysis of images of spatial cross sections of organisms taken with cellular lev...
Manjunatha Jagalur, Chris Pal, Erik G. Learned-Mil...
ICCAD
2006
IEEE
103views Hardware» more  ICCAD 2006»
15 years 6 months ago
A statistical framework for post-silicon tuning through body bias clustering
Adaptive body biasing (ABB) is a powerful technique that allows post-silicon tuning of individual manufactured dies such that each die optimally meets the delay and power constrai...
Sarvesh H. Kulkarni, Dennis Sylvester, David Blaau...