nical Abstract Optimization is to find the "best" solution to a problem where the quality of a solution can be measured by a given criterion. Estimation of Distribution A...
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on loc...
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...