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» Analysis of Random Noise and Random Walk Algorithms
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STOC
2009
ACM
99views Algorithms» more  STOC 2009»
14 years 8 months ago
Testing juntas nearly optimally
A function on n variables is called a k-junta if it depends on at most k of its variables. In this article, we show that it is possible to test whether a function is a k-junta or ...
Eric Blais
SODA
1997
ACM
115views Algorithms» more  SODA 1997»
13 years 9 months ago
On-Line Difference Maximization
In this paper we examine problems motivated by on-line financial problems and stochastic games. In particular, we consider a sequence of entirely arbitrary distinct values arrivin...
Ming-Yang Kao, Stephen R. Tate
CORR
2007
Springer
105views Education» more  CORR 2007»
13 years 8 months ago
Relative-Error CUR Matrix Decompositions
Many data analysis applications deal with large matrices and involve approximating the matrix using a small number of “components.” Typically, these components are linear combi...
Petros Drineas, Michael W. Mahoney, S. Muthukrishn...
GECCO
2009
Springer
14 years 19 days ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
EOR
2007
101views more  EOR 2007»
13 years 8 months ago
Optimizing an objective function under a bivariate probability model
The motivation of this paper is to obtain an analytical closed form of a quadratic objective function arising from a stochastic decision process with bivariate exponential probabi...
Xavier Brusset, Nico M. Temme