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» On regularization algorithms in learning theory
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NIPS
2008
15 years 6 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
POPL
2006
ACM
16 years 4 months ago
Polymorphic regular tree types and patterns
We propose a type system based on regular tree grammars, where algebraic datatypes are interpreted in a structural way. Thus, the same constructors can be reused for different typ...
Jerome Vouillon
IR
2007
15 years 4 months ago
Regularizing query-based retrieval scores
In information retrieval, the cluster hypothesis states: closely related documents tend to be relevant to the same request. We exploit this hypothesis directly by adjusting queryb...
Fernando Diaz
153
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HLK
2003
IEEE
15 years 9 months ago
Regularized 3D Morphable Models
Three-dimensional morphable models of object classes are a powerful tool in modeling, animation and recognition. We introduce here the new concept of regularized 3D morphable mode...
Curzio Basso, Thomas Vetter, Volker Blanz
ALT
2010
Springer
15 years 6 months ago
Distribution-Dependent PAC-Bayes Priors
We further develop the idea that the PAC-Bayes prior can be informed by the data-generating distribution. We prove sharp bounds for an existing framework of Gibbs algorithms, and ...
Guy Lever, François Laviolette, John Shawe-...