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» Machine-Learning Applications of Algorithmic Randomness
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ATAL
2007
Springer
14 years 2 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
JMLR
2010
152views more  JMLR 2010»
13 years 2 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
ECML
2006
Springer
13 years 11 months ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
11 years 10 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray
CICLING
2005
Springer
14 years 1 months ago
A Machine Learning Approach to Information Extraction
Information extraction is concerned with applying natural language processing to automatically extract the essential details from text documents. A great disadvantage of current ap...
Alberto Téllez-Valero, Manuel Montes-y-G&oa...