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» Parameterized Complexity and Approximation Algorithms
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COCOON
2005
Springer
15 years 3 months ago
Algorithmic and Complexity Issues of Three Clustering Methods in Microarray Data Analysis
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray ...
Jinsong Tan, Kok Seng Chua, Louxin Zhang
ICALP
2010
Springer
15 years 2 days ago
Parameterized Modal Satisfiability
We investigate the parameterized computational complexity of the satisfiability problem for modal logic and attempt to pinpoint relevant structural parameters which cause the probl...
Antonis Achilleos, Michael Lampis, Valia Mitsou
ECAI
2004
Springer
15 years 1 months ago
Yet More Efficient EM Learning for Parameterized Logic Programs by Inter-Goal Sharing
Abstract. In previous research, we presented a dynamicprogramming-based EM (expectation-maximization) algorithm for parameterized logic programs, which is based on the structure sh...
Yoshitaka Kameya, Taisuke Sato, Neng-Fa Zhou
SODA
2000
ACM
132views Algorithms» more  SODA 2000»
14 years 11 months ago
Expected-case complexity of approximate nearest neighbor searching
Most research in algorithms for geometric query problems has focused on their worstcase performance. However, when information on the query distribution is available, the alternat...
Sunil Arya, Ho-Yam Addy Fu
SBCCI
2003
ACM
129views VLSI» more  SBCCI 2003»
15 years 3 months ago
Hyperspectral Images Clustering on Reconfigurable Hardware Using the K-Means Algorithm
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...
Abel Guilhermino S. Filho, Alejandro César ...