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KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 7 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
CEC
2008
IEEE
16 years 1 months ago
Auto-tuning fuzzy granulation for evolutionary optimization
—Much of the computational complexity in employing evolutionary algorithms as optimization tool is due to the fitness function evaluation that may either not exist or be computat...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
ICSM
2005
IEEE
16 years 5 days ago
An Empirical Comparison of Test Suite Reduction Techniques for User-Session-Based Testing of Web Applications
Automated cost-effective test strategies are needed to provide reliable, secure, and usable web applications. As a software maintainer updates an application, test cases must accu...
Sara Sprenkle, Sreedevi Sampath, Emily Gibson, Lor...
CIVR
2006
Springer
219views Image Analysis» more  CIVR 2006»
15 years 10 months ago
Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
CEC
2007
IEEE
15 years 8 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...