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» Smooth Optimization for Effective Multiple Kernel Learning
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ESA
2010
Springer
227views Algorithms» more  ESA 2010»
14 years 10 months ago
Approximating Parameterized Convex Optimization Problems
We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an -approximat...
Joachim Giesen, Martin Jaggi, Sören Laue
CVPR
2008
IEEE
15 years 11 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
15 years 2 months ago
Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of sma
Recent advances in genotyping technology have led to the generation of an enormous quantity of genetic data. Traditional methods of statistical analysis have proved insufficient i...
Emily Rose Holzinger, Carrie C. Buchanan, Scott M....
ICIP
2005
IEEE
15 years 11 months ago
Layered local prediction network with dynamic learning for face super-resolution
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Dahua Lin, Wei Liu, Xiaoou Tang
COLT
2010
Springer
14 years 7 months ago
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...
Alekh Agarwal, Ofer Dekel, Lin Xiao