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» Adaptive K-Means Clustering
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ICPR
2008
IEEE
15 years 4 months ago
Adaptive selection of non-target cluster centers for K-means tracker
Hua et al. have proposed a stable and efficient tracking algorithm called “K-means tracker”[2, 3, 5]. This paper describes an adaptive non-target cluster center selection met...
Hiroshi Oike, Haiyuan Wu, Toshikazu Wada
SIGIR
2004
ACM
15 years 3 months ago
Document clustering via adaptive subspace iteration
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
Tao Li, Sheng Ma, Mitsunori Ogihara
75
Voted
ICCAD
1994
IEEE
101views Hardware» more  ICCAD 1994»
15 years 1 months ago
A general framework for vertex orderings, with applications to netlist clustering
We present a general framework for the construction of vertex orderings for netlist clustering. Our WINDOW algorithm constructs an ordering by iteratively adding the vertex with h...
Charles J. Alpert, Andrew B. Kahng
ECML
2006
Springer
15 years 1 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi
KES
2005
Springer
15 years 3 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...