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» Monte Carlo simulation approach to stochastic programming
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ML
2008
ACM
150views Machine Learning» more  ML 2008»
15 years 6 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
EUROGP
2006
Springer
140views Optimization» more  EUROGP 2006»
15 years 9 months ago
Evolving Noisy Oscillatory Dynamics in Genetic Regulatory Networks
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
André Leier, P. Dwight Kuo, Wolfgang Banzha...
FPL
2010
Springer
139views Hardware» more  FPL 2010»
15 years 4 months ago
Mapping Multiple Multivariate Gaussian Random Number Generators on an FPGA
A Multivariate Gaussian random number generator (MVGRNG) is an essential block for many hardware designs, including Monte Carlo simulations. These simulations are usually used in a...
Chalermpol Saiprasert, Christos-Savvas Bouganis, G...
DATE
2009
IEEE
129views Hardware» more  DATE 2009»
16 years 22 days ago
Improved performance and variation modelling for hierarchical-based optimisation of analogue integrated circuits
A new approach in hierarchical optimisation is presented which is capable of optimising both the performance and yield of an analogue design. Performance and yield trade offs are ...
Sawal Ali, Li Ke, Reuben Wilcock, Peter Wilson
SIGGRAPH
1999
ACM
15 years 10 months ago
Modeling and Rendering of Weathered Stone
Stone is widespread in its use as a building material and artistic medium. One of its most remarkable qualities is that it changes appearance as it interacts with the environment....
Julie Dorsey, Alan Edelman, Henrik Wann Jensen, Ju...