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SIGGRAPH
1994
ACM
15 years 2 months ago
Using particles to sample and control implicit surfaces
We present a new particle-based approach to sampling and controlling implicit surfaces. A simple constraint locks a set of particles onto a surface while the particles and the sur...
Andrew P. Witkin, Paul S. Heckbert
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
14 years 11 months ago
An EDA based on local markov property and gibbs sampling
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
Siddhartha Shakya, Roberto Santana
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
14 years 8 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
87
Voted
SUTC
2010
IEEE
15 years 2 months ago
ASample: Adaptive Spatial Sampling in Wireless Sensor Networks
Abstract—A prominent application of Wireless Sensor Networks is the monitoring of physical phenomena. The value of the monitored attributes naturally depends on the accuracy of t...
Piotr Szczytowski, Abdelmajid Khelil, Neeraj Suri
ICIP
2007
IEEE
15 years 11 months ago
Epipolar Spaces and Optimal Sampling Strategies
If precise calibration information is unavailable, as is often the case for active binocular vision systems, the determination of epipolar lines becomes untenable. Yet, even witho...
James Monaco, Alan C. Bovik, Lawrence K. Cormack