Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
To develop effective learning algorithms for online cursive word recognition is still a challenge research issue. In this paper, we propose a probabilistic framework to model the ...