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» Adaptive Sampling for Noisy Problems
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CEC
2007
IEEE
14 years 2 months ago
A Utile Function Optimizer
Abstract— We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasi...
Christopher K. Monson, Kevin D. Seppi, James L. Ca...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 8 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
CSDA
2008
102views more  CSDA 2008»
13 years 7 months ago
Confidence intervals for the difference between two means
: Unit nonresponse and item nonresponse in sample surveys are a typical problem of nonresponse which can be handled by weighting adjustment and imputation methods, respectively. Th...
Weiwen Miao, Paul Chiou
SIGPRO
2010
122views more  SIGPRO 2010»
13 years 6 months ago
Parameter estimation for exponential sums by approximate Prony method
The recovery of signal parameters from noisy sampled data is a fundamental problem in digital signal processing. In this paper, we consider the following spectral analysis problem...
Daniel Potts, Manfred Tasche
CAV
2009
Springer
187views Hardware» more  CAV 2009»
14 years 8 months ago
A Markov Chain Monte Carlo Sampler for Mixed Boolean/Integer Constraints
We describe a Markov chain Monte Carlo (MCMC)-based algorithm for sampling solutions to mixed Boolean/integer constraint problems. The focus of this work differs in two points from...
Nathan Kitchen, Andreas Kuehlmann