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ISDA
2010
IEEE
14 years 9 months ago
Feature selection is the ReliefF for multiple instance learning
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...
ICPR
2010
IEEE
14 years 9 months ago
Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning
Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
Jeremy Bolton, Paul D. Gader
TACAS
2012
Springer
288views Algorithms» more  TACAS 2012»
13 years 7 months ago
Reduction-Based Formal Analysis of BGP Instances
Today’s Internet interdomain routing protocol, the Border Gateway Protocol (BGP), is increasingly complicated and fragile due to policy misconfigurations by individual autonomou...
Anduo Wang, Carolyn L. Talcott, Alexander J. T. Gu...
AI
2009
Springer
15 years 6 months ago
Cost-Based Sampling of Individual Instances
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
William Klement, Peter A. Flach, Nathalie Japkowic...
ICECCS
2006
IEEE
140views Hardware» more  ICECCS 2006»
15 years 5 months ago
Inference of Design Pattern Instances in UML models via Logic Programming
This paper formalizes the notion of a design model structurally conforming to a design pattern by representing the model as a logic program whilst the pattern as a query. The conf...
Dae-Kyoo Kim, Lunjin Lu