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115
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GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
15 years 3 months ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross
148
Voted
ICML
2010
IEEE
15 years 3 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
134
Voted
ML
2002
ACM
127views Machine Learning» more  ML 2002»
15 years 2 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
127
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CLOUDCOM
2010
Springer
15 years 23 days ago
Performing Large Science Experiments on Azure: Pitfalls and Solutions
Carrying out science at extreme scale is the next generational challenge facing the broad field of scientific research. Cloud computing offers to potential for an increasing number...
Wei Lu, Jared Jackson, Jaliya Ekanayake, Roger S. ...
MP
2011
14 years 9 months ago
An FPTAS for minimizing the product of two non-negative linear cost functions
We consider a quadratic programming (QP) problem (Π) of the form min xT Cx subject to Ax ≥ b where C ∈ Rn×n + , rank(C) = 1 and A ∈ Rm×n , b ∈ Rm . We present an FPTAS ...
Vineet Goyal, Latife Genç Kaya, R. Ravi