Add to ORKGThe principal focus of this thesis is the exploration of sparse structures in a variety of statistical modelling problems. While more comprehensive models can be useful to solve a larger number of problems, its calculation may be ill-posed in most practical instances because of the sparsity of informative features in the data. If this sparse structure can be exploited, the models can often be solved very efficiently. The thesis is composed of four projects. Firstly, feature sparsity is incorporated to improve the performance of support vector machines when there are a lot of noise features present. The second project is about an empirical study on how to construct an optimal cascade structure. The third project involves the design of a p...