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Displaying 1-4 out of 4 total
Mining the Web with Active Hidden Markov Models
Found in: Data Mining, IEEE International Conference on
By Tobias Scheffer, Christian Decomain, Stefan Wrobel
Issue Date:December 2001
pp. 645
No summary available.
   
Bias-free hypothesis evaluation in multirelational domains
Found in: Proceedings of the 2006 ACM symposium on Applied computing (SAC '06)
By Christine Korner, Stefan Wrobel
Issue Date:April 2006
pp. 639-640
In machine learning one typically assumes that the true classification of an object depends only on the object itself and given the object, is independent of the classification of other objects. In this case, setting aside a sufficiently large and randomly...
     
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning
Found in: Twenty-first international conference on Machine learning (ICML '04)
By Lourdes Pena Castillo, Stefan Wrobel
Issue Date:July 2004
pp. 182-182
Hill-climbing search is the most commonly used search algorithm in ILP systems because it permits the generation of theories in short running times. However, a well known drawback of this greedy search strategy is its myopia. Macro-operators (or macros for...
     
A sequential sampling algorithm for a general class of utility criteria
Found in: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '00)
By Stefan Wrobel, Tobias Scheffer
Issue Date:August 2000
pp. 330-334
With over 800 million pages covering most areas of human endeavor, the World-wide Web is a fertile ground for data mining research to make a difference to the effectiveness of information search. Today, Web surfers access the Web through two dominant inter...
     
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