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» Determining Consensus Numbers
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FLAIRS
2008
15 years 5 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
WSC
2007
15 years 5 months ago
Extension of the direct optimization algorithm for noisy functions
DIRECT (DIviding RECTangles) is a deterministic global optimization algorithm for bound-constrained problems. The algorithm, based on a space-partitioning scheme, performs both gl...
Geng Deng, Michael C. Ferris
ECIS
2001
15 years 4 months ago
Market Analysis of Electronic Business in Switzerland and Comparisons with Europe
A representative market study was carried out to determine the penetration of electronic business in Swiss companies. A random sample was used in which companies were classified b...
Andreas Meier, Stefan Hüsemann, Ambros Lü...
UAI
2004
15 years 4 months ago
Similarity-Driven Cluster Merging Method for Unsupervised Fuzzy Clustering
In this paper, a similarity-driven cluster merging method is proposed for unsupervised fuzzy clustering. The cluster merging method is used to resolve the problem of cluster valid...
Xuejian Xiong, Kap Luk Chan
WSC
2004
15 years 4 months ago
Approximating Free Exercise Boundaries for American-Style Options Using Simulation and Optimization
Monte Carlo simulation can be readily applied to asset pricing problems with multiple state variables and possible path dependencies because convergence of Monte Carlo methods is ...
Barry R. Cobb, John M. Charnes