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CGO
2009
IEEE
15 years 4 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
PR
2006
111views more  PR 2006»
14 years 9 months ago
An adaptive error penalization method for training an efficient and generalized SVM
A novel training method has been proposed for increasing efficiency and generalization of support vector machine (SVM). The efficiency of SVM in classification is directly determi...
Yiqiang Zhan, Dinggang Shen
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 9 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
NN
2006
Springer
14 years 9 months ago
Machine learning in soil classification
In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the cons...
Biswanath Bhattacharya, Dimitri P. Solomatine
ICML
2005
IEEE
15 years 10 months ago
Learning hierarchical multi-category text classification models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Craig Saunders, John Shawe-Taylor, Juho Rousu, S&a...