Stochastic perturbation methods can be applied to problems for which either the objective function is represented analytically, or the objective function is the result of a simula...
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
We introduce a new family of positive-definite kernels for large margin classification in support vector machines (SVMs). These kernels mimic the computation in large neural netwo...
In some expensive multiobjective optimization problems, several function evaluations can be carried out at one time. Therefore, it is very desirable to develop methods which can g...
Qingfu Zhang, Wudong Liu, Edward P. K. Tsang, Boto...
Abstract--This correspondence considers the problem of robust waveform design in the presence of colored Gaussian disturbance under a similarity and an energy constraint. We resort...