Shihai Wang

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Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learning with various strategies. To our knowledge, however, none of them takes all three semi-supervised assumptions, i.e., smoothness, cluster, and manifold assumptions, together into(More)
—Software faults could cause serious system errors and failures, leading to huge economic losses. But currently none of inspection and verification technique is able to find and eliminate all software faults. Software testing is an important way to inspect these faults and raise software reliability, but obviously it is a really expensive job. The(More)