Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
Properties of ensemble classification can be studied using the framework of Monte Carlo stochastic algorithms. Within this framework it is also possible to define a new ensemble c...
In this paper, we propose a linear control model for gene intervention in a genetic regulatory network. At each time step, finite controls are allowed to drive the network states...
Shuqin Zhang, Michael K. Ng, Wai-Ki Ching, Tatsuya...
In this paper a new concept of robustness is introduced and the corresponding optimization problem is stated. This new concept is applied to transportation network designs in which...
We develop a penalized kernel smoothing method for the problem of selecting nonzero elements of the conditional precision matrix, known as conditional covariance selection. This p...