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COLT
2008
Springer
14 years 19 days ago
Dimension and Margin Bounds for Reflection-invariant Kernels
A kernel over the Boolean domain is said to be reflection-invariant, if its value does not change when we flip the same bit in both arguments. (Many popular kernels have this prop...
Thorsten Doliwa, Michael Kallweit, Hans-Ulrich Sim...
IWPEC
2009
Springer
14 years 5 months ago
A Probabilistic Approach to Problems Parameterized above or below Tight Bounds
We introduce a new approach for establishing fixed-parameter tractability of problems parameterized above tight lower bounds or below tight upper bounds. To illustrate the approac...
Gregory Gutin, Eun Jung Kim, Stefan Szeider, Ander...
NIPS
2003
14 years 6 days ago
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
The decision functions constructed by support vector machines (SVM’s) usually depend only on a subset of the training set—the so-called support vectors. We derive asymptotical...
Ingo Steinwart
CDC
2009
IEEE
221views Control Systems» more  CDC 2009»
14 years 2 months ago
Parametrization invariant covariance quantification in identification of transfer functions for linear systems
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
Tzvetan Ivanov, Michel Gevers
NIPS
2001
14 years 7 days ago
Kernel Machines and Boolean Functions
We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
Adam Kowalczyk, Alex J. Smola, Robert C. Williamso...