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» Analysis of Random Noise and Random Walk Algorithms
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STOC
2009
ACM
99views Algorithms» more  STOC 2009»
16 years 2 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
115
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SODA
1997
ACM
115views Algorithms» more  SODA 1997»
15 years 3 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
124
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CORR
2007
Springer
105views Education» more  CORR 2007»
15 years 1 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
15 years 6 months 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»
15 years 1 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