We study how the dependence of a simulation output on an uncertain parameter can be determined, when simulations are computationally expensive and so can only be run for very few p...
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...
Daniel Tarlow, Ryan Prescott Adams, Richard S. Zem...
This paper presents novel likelihood estimation to be used for particle filter based object tracking. The likelihood estimation is built upon cascade object detector trained with ...
A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connecte...
In this paper, a fuzzy wavelet neural network model is proposed for system identification problems. The proposed model is obtained from the traditional Takagi-Sugeno-Kang (TSK) fu...