Multitask multiclass privileged information support vector machines

In this paper, we propose a new learning paradigm named multitask multiclass privileged information support vector machines. The starting point of our work is mainly based on the success of multitask multiclass support vector machines which cast multitask multiclass problems as a constrained optimization problem with a quadratic objective function. Learning using privileged information is an advanced learning paradigm integrated with the idea of human teaching in machine learning. This paper mainly extends multitask multi-class support vector machines to privileged information learning strategy. Our approach can take full advantages of the multitask learning and privileged information. Experimental results show that our approaches obtains very good results for multitask multiclass problems.