SADM
2010
13 years 7 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
EWC
2010
13 years 9 months ago
2010
Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, findin...
MOR
2007
13 years 12 months ago
2007
We consider a generalization of the model of stochastic search in an out-forest, introduced and studied by Denardo, Rothblum, and Van der Heyden [1]. We provide a simple proof of ...
SYNTHESE
2008
2008
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
14 years 10 days ago
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
AAAI
2000
14 years 1 months ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
ECAI
2006
Springer
14 years 4 months ago
2006
Springer
Some of the most successful algorithms for satisfiability, such as Walksat, are based on random walks. Similarly, local search algorithms for solving constraint optimization proble...
GECCO
2003
Springer
14 years 5 months ago
2003
Springer
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...