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JMLR
2010
121views more  JMLR 2010»
14 years 11 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
JMLR
2010
152views more  JMLR 2010»
14 years 11 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...
JMLR
2010
161views more  JMLR 2010»
14 years 11 months ago
Empirical Bernstein Boosting
Concentration inequalities that incorporate variance information (such as Bernstein's or Bennett's inequality) are often significantly tighter than counterparts (such as...
Pannagadatta K. Shivaswamy, Tony Jebara
TCBB
2010
112views more  TCBB 2010»
14 years 11 months ago
A Study of Hierarchical and Flat Classification of Proteins
Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that e...
Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan ...
TIFS
2010
137views more  TIFS 2010»
14 years 11 months ago
On the dynamic selection of biometric fusion algorithms
Biometric fusion consolidates the output of multiple biometric classifiers to render a decision about the identity of an individual. We consider the problem of designing a fusion s...
Mayank Vatsa, Richa Singh, Afzel Noore, Arun Ross