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ICCV
2009
IEEE
13 years 5 months ago
Kernel map compression using generalized radial basis functions
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Omar Arif, Patricio A. Vela
JMLR
2010
187views more  JMLR 2010»
13 years 2 months ago
SFO: A Toolbox for Submodular Function Optimization
In recent years, a fundamental problem structure has emerged as very useful in a variety of machine learning applications: Submodularity is an intuitive diminishing returns proper...
Andreas Krause
TIP
2010
277views more  TIP 2010»
13 years 2 months ago
Distance Regularized Level Set Evolution and Its Application to Image Segmentation
Level set methods have been widely used in image processing and computer vision. In conventional level set formulations, the level set function typically develops irregularities du...
Chunming Li, Chenyang Xu, Changfeng Gui, Martin D....
TOMACS
2010
79views more  TOMACS 2010»
13 years 2 months ago
A stochastic approximation method with max-norm projections and its applications to the Q-learning algorithm
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
Sumit Kunnumkal, Huseyin Topaloglu
ISCI
2011
13 years 2 months ago
Aggregation functions: Construction methods, conjunctive, disjunctive and mixed classes
In this second part of our state-of-the-art overview on aggregation theory, based again on our recent monograph on aggregation functions, we focus on several construction methods ...
Michel Grabisch, Jean-Luc Marichal, Radko Mesiar, ...