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GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
14 years 1 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
NIPS
2004
13 years 11 months ago
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms
In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We exp...
Omid Madani, David M. Pennock, Gary William Flake
IJON
2006
146views more  IJON 2006»
13 years 10 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
WSC
2008
14 years 9 days ago
Creating and using non-kinetic effects: Training joint forces for asymmetric operations
US military forces now face asymmetric military operations. Management of relationships with civilians is often crucial to success. Local population groups can provide critical in...
Hugh Henry, Robert G. Chamberlain
ICASSP
2011
IEEE
13 years 1 months ago
Nonstationary and temporally correlated source separation using Gaussian process
Blind source separation (BSS) is a process to reconstruct source signals from the mixed signals. The standard BSS methods assume a fixed set of stationary source signals with the ...
Hsin-Lung Hsieh, Jen-Tzung Chien