In this paper we develop a novel generalization bound for learning the kernel problem. First, we show that the generalization analysis of the kernel learning problem reduces to in...
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
View synthesis offers a great flexibility in generating free viewpoint television (FTV) and 3D video (3DV). However, the depth-image-based view synthesis approach is very sensiti...
Wenxiu Sun, Oscar C. Au, Lingfeng Xu, Sung Him Chu...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...