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» Unsupervised Problem Decomposition Using Genetic Programming
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DAM
2007
91views more  DAM 2007»
13 years 11 months ago
Integer linear programming approaches for non-unique probe selection
In addition to their prevalent use for analyzing gene expression, DNA microarrays are an efficient tool for biological, medical, and industrial applications because of their abil...
Gunnar W. Klau, Sven Rahmann, Alexander Schliep, M...
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 4 months ago
Preventing overfitting in GP with canary functions
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
Nate Foreman, Matthew P. Evett
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
14 years 5 months ago
Interactive evolution of XUL user interfaces
We attack the problem of user fatigue by using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algori...
Juan C. Quiroz, Sushil J. Louis, Sergiu M. Dascalu
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
14 years 5 months ago
A systemic computation platform for the modelling and analysis of processes with natural characteristics
Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1]...
Erwan Le Martelot, Peter J. Bentley, R. Beau Lotto
CVPR
2012
IEEE
12 years 1 months ago
Generalized Multiview Analysis: A discriminative latent space
This paper presents a general multi-view feature extraction approach that we call Generalized Multiview Analysis or GMA. GMA has all the desirable properties required for cross-vi...
Abhishek Sharma, Abhishek Kumar, Hal Daumé ...