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SIGCSE
2000
ACM
91views Education» more  SIGCSE 2000»
15 years 9 months ago
Machine learning in the liberal arts curriculum
Machine learning is typically considered a graduate-level course with an artificial intelligence course as a prerequisite. However, it does not need to be positioned this way, and...
Clare Bates Congdon
ICMLA
2007
15 years 6 months ago
Machine learned regression for abductive DNA sequencing
We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
David Thornley, Maxim Zverev, Stavros Petridis
IJCAI
1989
15 years 6 months ago
An Empirical Comparison of Pattern Recognition, Neural Nets, and Machine Learning Classification Methods
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
Sholom M. Weiss, Ioannis Kapouleas
ESANN
2007
15 years 6 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
TNN
2008
101views more  TNN 2008»
15 years 5 months ago
Comments on "The Extreme Learning Machine"
Abstract--This comment letter points out that the essence of the "extreme learning machine (ELM)" recently appeared has been proposed earlier by Broomhead and Lowe and Pa...
L. P. Wang, C. R. Wan