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» Generalization Bounds for Learning Kernels
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ICML
2010
IEEE
13 years 9 months ago
Robust Formulations for Handling Uncertainty in Kernel Matrices
We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we ...
Sahely Bhadra, Sourangshu Bhattacharya, Chiranjib ...
COLT
2007
Springer
14 years 2 months ago
Occam's Hammer
Abstract. We establish a generic theoretical tool to construct probabilistic bounds for algorithms where the output is a subset of objects from an initial pool of candidates (or mo...
Gilles Blanchard, François Fleuret
COLT
1999
Springer
14 years 23 days ago
Drifting Games
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Robert E. Schapire
ICASSP
2007
IEEE
14 years 2 months ago
Kernel Resolution Synthesis for Superresolution
Abstract— This work considers a combination classificationregression based framework with the proposal of using learned kernels in modified support vector regression to provide...
Karl S. Ni, Truong Nguyen
COLT
2005
Springer
14 years 2 months ago
Localized Upper and Lower Bounds for Some Estimation Problems
Abstract. We derive upper and lower bounds for some statistical estimation problems. The upper bounds are established for the Gibbs algorithm. The lower bounds, applicable for all ...
Tong Zhang