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» A distributed machine learning framework
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131
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UAI
2001
15 years 2 months ago
Markov Chain Monte Carlo using Tree-Based Priors on Model Structure
We present a general framework for defining priors on model structure and sampling from the posterior using the Metropolis-Hastings algorithm. The key ideas are that structure pri...
Nicos Angelopoulos, James Cussens
84
Voted
ECML
2005
Springer
15 years 6 months ago
Severe Class Imbalance: Why Better Algorithms Aren't the Answer
This paper argues that severe class imbalance is not just an interesting technical challenge that improved learning algorithms will address, it is much more serious. To be useful, ...
Chris Drummond, Robert C. Holte
94
Voted
IEEECIT
2010
IEEE
14 years 11 months ago
Scaling the iHMM: Parallelization versus Hadoop
—This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facilit...
Sebastien Bratieres, Jurgen Van Gael, Andreas Vlac...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 1 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
88
Voted
ALT
2003
Springer
15 years 9 months ago
Learning a Subclass of Regular Patterns in Polynomial Time
An algorithm for learning a subclass of erasing regular pattern languages is presented. On extended regular pattern languages generated by patterns π of the form x0α1x1 . . . α...
John Case, Sanjay Jain, Rüdiger Reischuk, Fra...