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KI
2007
Springer
13 years 7 months ago
Improving the Detection of Unknown Computer Worms Activity Using Active Learning
Detecting unknown worms is a challenging task. Extant solutions, such as anti-virus tools, rely mainly on prior explicit knowledge of specific worm signatures. As a result, after t...
Robert Moskovitch, Nir Nissim, Dima Stopel, Clint ...
NIPS
1996
13 years 9 months ago
Radial Basis Function Networks and Complexity Regularization in Function Learning
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function netwo...
Adam Krzyzak, Tamás Linder
SIAMJO
2002
99views more  SIAMJO 2002»
13 years 7 months ago
Active Sets, Nonsmoothness, and Sensitivity
Nonsmoothness pervades optimization, but the way it typically arises is highly structured. Nonsmooth behavior of an objective function is usually associated, locally, with an activ...
A. S. Lewis
IJCV
2006
262views more  IJCV 2006»
13 years 7 months ago
A Variational Model for Object Segmentation Using Boundary Information and Shape Prior Driven by the Mumford-Shah Functional
In this paper, we propose a new variational model to segment an object belonging to a given shape space using the active contour method, a geometric shape prior and the Mumford-Sha...
Xavier Bresson, Pierre Vandergheynst, Jean-Philipp...
ISCI
2008
95views more  ISCI 2008»
13 years 7 months ago
Modified constrained learning algorithms incorporating additional functional constraints into neural networks
In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...
Fei Han, Qing-Hua Ling, De-Shuang Huang