173views more  SADM 2010»
12 years 11 months ago
Data reduction in classification: A simulated annealing based projection method
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...
Tian Siva Tian, Rand R. Wilcox, Gareth M. James
178views more  EWC 2010»
13 years 1 months ago
Design of tensegrity structures using parametric analysis and stochastic search
Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, findin...
Landolf Rhode-Barbarigos, Himanshu Jain, Prakash K...
99views more  MOR 2007»
13 years 3 months ago
Stochastic Search in a Forest Revisited
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 ...
Jay Sethuraman, John N. Tsitsiklis
84views more  SYNTHESE 2008»
13 years 4 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
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...
Thomas Bartz-Beielstein
13 years 5 months ago
Localizing Search in Reinforcement Learning
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 ...
Gregory Z. Grudic, Lyle H. Ungar
13 years 7 months ago
Random Subset Optimization
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...
Boi Faltings, Quang Huy Nguyen
268views Optimization» more  GECCO 2003»
13 years 9 months ago
A Generalized Feedforward Neural Network Architecture and Its Training Using Two Stochastic Search Methods
Shunting Inhibitory Artificial Neural Networks (SIANNs) are biologically inspired networks in which the synaptic interactions are mediated via a nonlinear mechanism called shuntin...
Abdesselam Bouzerdoum, Rainer Mueller