Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
— We consider a ring topology with limited or full switching capability as deployed in high bandwidth metro optical networks and develop a model to estimate the probability of bl...
Consider a database most of whose entries are marked but the precise fraction of marked entries is not known. What is known is that the fraction of marked entries is 1 − , where ...
Optimal solutions to Markov Decision Problems (MDPs) are very sensitive with respect to the state transition probabilities. In many practical problems, the estimation of those pro...
: Probabilistic Boolean Network (PBN) is widely used to model genetic regulatory networks. Evolution of the PBN is according to the transition probability matrix. Steady-state (lon...
Shuqin Zhang, Wai-Ki Ching, Michael K. Ng, Tatsuya...