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JMLR
2010
121views more  JMLR 2010»
13 years 3 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
CVPR
2010
IEEE
14 years 4 days ago
Discriminative K-SVD for Dictionary Learning in Face Recognition
In a sparse-representation-based face recognition scheme, the desired dictionary should have good representational power (i.e., being able to span the subspace of all faces) while...
Qiang Zhang, Baoxin Li
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
14 years 3 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
SCVMA
2004
Springer
14 years 2 months ago
3D SSD Tracking from Uncalibrated Video
Abstract. In registration-based tracking precise pose between a reference template and the current image is determined by warping image patches into the template coordinates and ma...
Dana Cobzas, Martin Jägersand
GECCO
2010
Springer
150views Optimization» more  GECCO 2010»
14 years 1 months ago
Object-level recombination of commodity applications
This paper presents ObjRecombGA, a genetic algorithm framework for recombining related programs at the object file level. A genetic algorithm guides the selection of object file...
Blair Foster, Anil Somayaji