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CORR
2000
Springer
120views Education» more  CORR 2000»
13 years 8 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
WWW
2002
ACM
14 years 9 months ago
A machine learning based approach for table detection on the web
Table is a commonly used presentation scheme, especially for describing relational information. However, table understanding remains an open problem. In this paper, we consider th...
Yalin Wang, Jianying Hu
IFIP12
2008
13 years 10 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
SIGMOD
2004
ACM
199views Database» more  SIGMOD 2004»
14 years 8 months ago
Approximate XML Query Answers
The rapid adoption of XML as the standard for data representation and exchange foreshadows a massive increase in the amounts of XML data collected, maintained, and queried over th...
Neoklis Polyzotis, Minos N. Garofalakis, Yannis E....
ICCV
2009
IEEE
15 years 1 months ago
Efficient subset selection based on the Renyi entropy
Many machine learning algorithms require the summation of Gaussian kernel functions, an expensive operation if implemented straightforwardly. Several methods have been proposed t...
Vlad I. Morariu1, Balaji V. Srinivasan, Vikas C. R...