The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Domain knowledge is essential for successful problem solving and optimization. This paper introduces a framework in which a form of automatic domain knowledge extraction can be im...
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
We consider the sparse grid combination technique for regression, which we regard as a problem of function reconstruction in some given function space. We use a regularised least ...
To learn a new visual category from few examples, prior knowledge from unlabeled data as well as previous related categories may be useful. We develop a new method for transfer le...