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IJCNN
2007
IEEE
13 years 12 months ago
Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent
—The 0/1 loss is an important cost function for perceptrons. Nevertheless it cannot be easily minimized by most existing perceptron learning algorithms. In this paper, we propose...
Ling Li, Hsuan-Tien Lin
COMBINATORICS
2000
91views more  COMBINATORICS 2000»
13 years 5 months ago
On Descents in Standard Young Tableaux
In this paper, explicit formulae for the expectation and the variance of descent functions on random standard Young tableaux are presented. Using these, it is shown that the norma...
Peter A. Hästö
CORR
2008
Springer
97views Education» more  CORR 2008»
13 years 5 months ago
Posets and Permutations in the Duplication-Loss Model: Minimal Permutations with d Descents
In this paper, we are interested in the combinatorial analysis of the whole genome duplication - random loss model of genome rearrangement initiated in [8] and [7]. In this model,...
Mathilde Bouvel, Elisa Pergola
RTA
2007
Springer
13 years 11 months ago
Random Descent
Vincent van Oostrom
CORR
2007
Springer
111views Education» more  CORR 2007»
13 years 5 months ago
Circumspect descent prevails in solving random constraint satisfaction problems
Mikko Alava, John Ardelius, Erik Aurell, Petteri K...