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IJCAI
1989
15 years 8 days ago
A Study of Empirical Learning for an Involved Problem
In real-world domains a concept to be learned may be unwieldy and the environment may be less than ideal. One combination of difficulties occurs if the concept is probabilistic an...
Larry A. Rendell
COLCOM
2005
IEEE
15 years 4 months ago
Developing a framework for integrating prior problem solving and knowledge sharing histories of a group to predict future group
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
BMCBI
2010
140views more  BMCBI 2010»
14 years 8 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
ILP
2005
Springer
15 years 4 months ago
Machine Learning for Systems Biology
In this paper we survey work being conducted at Imperial College on the use of machine learning to build Systems Biology models of the effects of toxins on biochemical pathways. Se...
Stephen Muggleton
SSPR
2004
Springer
15 years 4 months ago
Learning People Movement Model from Multiple Cameras for Behaviour Recognition
Abstract. In surveillance systems for monitoring people behaviour, it is imporant to build systems that can adapt to the signatures of the people tasks and movements in the environ...
Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. We...