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ML
2006
ACM
110views Machine Learning» more  ML 2006»
13 years 7 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
13 years 11 months ago
Evolution of Goal-Directed Behavior from Limited Information in a Complex Environment
In this paper, we apply an evolutionary algorithm to learning behavior on a novel, interesting task to explore the general issue of learning e ective behaviors in a complex enviro...
Matthew R. Glickman, Katia P. Sycara
BIBE
2007
IEEE
162views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning
— The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. We are investigating the possibility of de...
Mary Qu Yang, Jack Y. Yang
GECCO
2009
Springer
188views Optimization» more  GECCO 2009»
13 years 11 months ago
Exploiting multiple classifier types with active learning
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
Zhenyu Lu, Josh Bongard
BMCBI
2006
152views more  BMCBI 2006»
13 years 7 months ago
A two-stage approach for improved prediction of residue contact maps
Background: Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure. Although improvemen...
Alessandro Vullo, Ian Walsh, Gianluca Pollastri