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174
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ILP
2001
Springer
15 years 11 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
ICANN
2009
Springer
15 years 10 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
191
Voted
ICANN
2009
Springer
15 years 10 months ago
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao
CIKM
1995
Springer
15 years 10 months ago
Learning Subjective Relevance to Facilitate Information Access
As the amount of available electronic information is dramatically increasing, the ability for rapid and e ective access to information has become critical. Most traditional inform...
James R. Chen, Nathalie Mathe
ECCV
2010
Springer
15 years 9 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...