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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...
ICASSP
2011
IEEE
12 years 11 months ago
Effective background data selection in SVM speaker recognition for unseen test environment: More is not always better
This study focuses on determining a procedure to select effective negative examples for development of improved Support Vector Machine (SVM) based speaker recognition. Selection o...
Jun-Won Suh, Yun Lei, Wooil Kim, John H. L. Hansen
COLT
2001
Springer
13 years 12 months ago
Limitations of Learning via Embeddings in Euclidean Half-Spaces
The notion of embedding a class of dichotomies in a class of linear half spaces is central to the support vector machines paradigm. We examine the question of determining the mini...
Shai Ben-David, Nadav Eiron, Hans-Ulrich Simon
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
13 years 5 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
BMCBI
2010
208views more  BMCBI 2010»
13 years 7 months ago
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene
Background: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tr...
Zafer Aydin, John I. Murray, Robert H. Waterston, ...