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» FPT algorithms and kernels for the Directed k-Leaf problem
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NIPS
2008
13 years 10 months ago
Learning with Consistency between Inductive Functions and Kernels
Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
Haixuan Yang, Irwin King, Michael R. Lyu
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
14 years 6 days ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
WADS
2009
Springer
232views Algorithms» more  WADS 2009»
14 years 3 months ago
On Making Directed Graphs Transitive
We present the first thorough theoretical analysis of the Transitivity Editing problem on digraphs. Herein, the task is to perform a minimum number of arc insertions or deletions ...
Mathias Weller, Christian Komusiewicz, Rolf Nieder...
ISNN
2007
Springer
14 years 2 months ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang
SODA
2010
ACM
261views Algorithms» more  SODA 2010»
14 years 6 months ago
Bidimensionality and Kernels
Bidimensionality theory appears to be a powerful framework in the development of meta-algorithmic techniques. It was introduced by Demaine et al. [J. ACM 2005 ] as a tool to obtai...
Fedor V. Fomin, Daniel Lokshtanov, Saket Saurabh, ...