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ICONIP
2008
13 years 9 months ago
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Alexandra Scherbart, Tim W. Nattkemper
ICML
2006
IEEE
14 years 8 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
JMLR
2006
137views more  JMLR 2006»
13 years 7 months ago
Bounds for Linear Multi-Task Learning
Abstract. We give dimension-free and data-dependent bounds for linear multi-task learning where a common linear operator is chosen to preprocess data for a vector of task speci...c...
Andreas Maurer
RECOMB
2005
Springer
14 years 8 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
SDM
2010
SIAM
259views Data Mining» more  SDM 2010»
13 years 9 months ago
Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...
Pavel P. Kuksa, Yanjun Qi