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» Convex Programming Methods for Global Optimization
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JMLR
2010
121views more  JMLR 2010»
13 years 2 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
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
MP
2006
105views more  MP 2006»
13 years 7 months ago
Two-stage integer programs with stochastic right-hand sides: a superadditive dual approach
We consider two-stage pure integer programs with discretely distributed stochastic right-hand sides. We present an equivalent superadditive dual formulation that uses the value fun...
Nan Kong, Andrew J. Schaefer, Brady Hunsaker
MP
2008
99views more  MP 2008»
13 years 7 months ago
Efficient robust optimization for robust control with constraints
This paper proposes an efficient computational technique for the optimal control of linear discrete-time systems subject to bounded disturbances with mixed polytopic constraints o...
Paul J. Goulart, Eric C. Kerrigan, Daniel Ralph
ICASSP
2011
IEEE
12 years 11 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li