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Tutorials
Abstract
This tutorial will present the current state of research on Web people
searches. It will be mainly about person name disambiguation
problems, and the attribute extraction methods that can be used to
support person name disambiguation. We shall give a survey of the
algorithms and tools available, and discuss the possibility of
applying machine learning to this problem. A survey of WePS workshops
dedicated to this task will also be presented.
Tutorial homepage
Abstract
The objective of the tutorial is to give an overview on validation
methods of supervised classification algorithms. The tutorial starts
by presenting the most common performance measures used to evaluate
supervised learning algorithm. After that the methods used to estimate
the previous measures will be described in detail. We will also expose
the statistical tests that can be used to compare several supervised
classification algorithms. The tutorial concludes by giving
recommendations to perform honest classifier evaluation according to
specific characteristics of the problem or the data set at hand as
well as general best practices in classifier evaluation.
Tutorial homepage
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Support Vector Machines and Kernel Methods: Status and Challenges
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Chih-Jen Lin
National Taiwan University, Taiwan
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Abstract
Support vector machines (SVM) and kernel methods are now important
machine learning techniques. In this tutorial, we first introduce
some basic concepts such as maximal margin, kernel mappings, and primal
dual relationships. We then discuss the training by solving
optimization problems and the selection of parameters. Finally, we
briefly mention some new research issues.
Tutorial homepage
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