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» Using Gaussian Processes to Optimize Expensive Functions
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EOR
2007
101views more  EOR 2007»
13 years 7 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
ICIP
2006
IEEE
14 years 9 months ago
Sparse Image Reconstruction for Partially known Blur Functions
In this paper, we consider the problem of image reconstruction from the noisy blurred version of an original image when the blurring operator is partially known and the original i...
Raviv Raich, Alfred O. Hero
ISORC
1998
IEEE
13 years 12 months ago
Automating Regression Testing for Real-Time Software in a Distributed Environment
Many real-time systems evolve over time due to new requirements and technology improvements. Each revision requires regression testing to ensure that existing functionality is not...
Feng Zhu, Sanjai Rayadurgam, Wei-Tek Tsai
AUSAI
2009
Springer
13 years 11 months ago
Classification-Assisted Memetic Algorithms for Equality-Constrained Optimization Problems
Regressions has successfully been incorporated into memetic algorithm (MA) to build surrogate models for the objective or constraint landscape of optimization problems. This helps ...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...
DATE
2005
IEEE
115views Hardware» more  DATE 2005»
14 years 1 months ago
Functional Coverage Driven Test Generation for Validation of Pipelined Processors
Functional verification of microprocessors is one of the most complex and expensive tasks in the current system-on-chip design process. A significant bottleneck in the validatio...
Prabhat Mishra, Nikil D. Dutt