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IJHIS
2006
94views more  IJHIS 2006»
14 years 9 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
ML
2006
ACM
163views Machine Learning» more  ML 2006»
14 years 9 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
CVPR
2007
IEEE
15 years 11 months ago
Trace Ratio vs. Ratio Trace for Dimensionality Reduction
A large family of algorithms for dimensionality reduction end with solving a Trace Ratio problem in the form of arg maxW Tr(WT SpW)/Tr(WT SlW)1 , which is generally transformed in...
Huan Wang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Th...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
IJCAI
2003
14 years 10 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...