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» Selection of Subsets of Ordered Features in Machine Learning
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GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 10 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
ISAAC
2000
Springer
178views Algorithms» more  ISAAC 2000»
15 years 7 months ago
Simple Algorithms for a Weighted Interval Selection Problem
Given a set of jobs, each consisting of a number of weighted intervals on the real line, and a number m of machines, we study the problem of selecting a maximum weight subset of th...
Thomas Erlebach, Frits C. R. Spieksma
TSC
2008
140views more  TSC 2008»
15 years 3 months ago
Dynamic Web Service Selection for Reliable Web Service Composition
This paper studies the dynamic Web service selection problem in a failure-prone environment, which aims to determine a subset of Web services to be invoked at runtime so as to succ...
San-Yih Hwang, Ee-Peng Lim, Chien-Hsiang Lee, Chen...
ICASSP
2011
IEEE
14 years 7 months ago
A kernelized maximal-figure-of-merit learning approach based on subspace distance minimization
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Byungki Byun, Chin-Hui Lee
120
Voted
ICDM
2007
IEEE
96views Data Mining» more  ICDM 2007»
15 years 10 months ago
The Chosen Few: On Identifying Valuable Patterns
Constrained pattern mining extracts patterns based on their individual merit. Usually this results in far more patterns than a human expert or a machine learning technique could m...
Björn Bringmann, Albrecht Zimmermann