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ML
2008
ACM
13 years 7 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
ICML
1999
IEEE
14 years 8 months ago
Making Better Use of Global Discretization
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Eibe Frank, Ian H. Witten
IROS
2009
IEEE
145views Robotics» more  IROS 2009»
14 years 2 months ago
Utilizing prior information to enhance self-supervised aerial image analysis for extracting parking lot structures
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
Young-Woo Seo, Chris Urmson
ICML
2002
IEEE
14 years 8 months ago
Adaptive View Validation: A First Step Towards Automatic View Detection
Multi-view algorithms reduce the amount of required training data by partitioning the domain features into separate subsets or views that are sufficient to learn the target concep...
Ion Muslea, Steven Minton, Craig A. Knoblock
CIKM
2005
Springer
14 years 1 months ago
Learning to summarise XML documents using content and structure
Documents formatted in eXtensible Markup Language (XML) are becoming increasingly available in collections of various document types. In this paper, we present an approach for the...
Massih-Reza Amini, Anastasios Tombros, Nicolas Usu...