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CP
2010
Springer
13 years 6 months ago
An Empirical Study of Optimization for Maximizing Diffusion in Networks
Abstract. We study the problem of maximizing the amount of stochastic diffusion in a network by acquiring nodes within a certain limited budget. We use a Sample Average Approximati...
Kiyan Ahmadizadeh, Bistra N. Dilkina, Carla P. Gom...
CORR
2002
Springer
132views Education» more  CORR 2002»
13 years 8 months ago
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Marco Zaffalon, Marcus Hutter
TVCG
2008
192views more  TVCG 2008»
13 years 8 months ago
Anisotropic Noise Samples
We present a practical approach to generate stochastic anisotropic samples with Poisson-disk characteristic over a two-dimensional domain. In contrast to isotropic samples, we unde...
Louis Feng, Ingrid Hotz, Bernd Hamann, Kenneth I. ...
AAAI
2004
13 years 10 months ago
SOFIA's Choice: An AI Approach to Scheduling Airborne Astronomy Observations
We describe an innovative solution to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The probl...
Jeremy Frank, Michael A. K. Gross, Elif Kürkl...
NIPS
2007
13 years 10 months ago
Consistent Minimization of Clustering Objective Functions
Clustering is often formulated as a discrete optimization problem. The objective is to find, among all partitions of the data set, the best one according to some quality measure....
Ulrike von Luxburg, Sébastien Bubeck, Stefa...