We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
—Face recognition performance depends upon the input variability as encountered during biometric data capture including occlusion and disguise. The challenge met in this paper is...
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...