We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic alg...
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Based on the analysis of non-verbal inter-human interaction, this paper proposes a model for estimating human friendships in the presence of a humanoid robot. Our previous study i...
Fads models were introduced by Shiller (1984) and Summers (1986) as plausible alternatives to the efficient markets/constant expected returns assumptions. Under these models, loga...