Yunyun Wang

Learn More
The cluster assumption, which assumes that “similar instances should share the same label,” is a basic assumption in semi-supervised classification learning, and has been found very useful in many successful semi-supervised classification methods. It is rarely noticed that when the cluster assumption is adopted, there is an implicit assumption(More)
Aberrant microRNA (miRNA) expression contributes to a series of malignant cancer behaviors, including radioresistance. Our previous study showed differential expression of miR-185-3p in post-radiation nasopharyngeal carcinoma (NPC) cells. To investigate the role of miR-185-3p in NPC radioresistance, CNE-2 and 5-8F cells were transfected with miR-185-3p(More)
Though semi-supervised classification learning has attracted great attention over past decades, semi-supervised classification methods may show worse performance than their supervised counterparts in some cases, consequently reducing their confidence in real applications. Naturally, it is desired to develop a safe semi-supervised classification method that(More)
Pairwise constraint propagation studies the problem of propagating the scarce pairwise constraints across the entire dataset. Effective propagation algorithms have previously been designed based on the graph-based semi-supervised learning framework. Therefore, these previous constraint propagation methods rely critically on a good similarity measure over(More)
BACKGROUND Many evidences show the inverse correlation between helminth infection and allergic or autoimmune diseases. Identification and characterization of the active helminth-derived products responsible for the beneficial effects on allergic or inflammatory diseases will provide another feasible approach to treat these diseases. METHODS AND FINDINGS(More)
AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample pairs playing the same roles as the support vector samples in SVM. Such a learning paradigm generally emphasizes more on the local discriminative information just associated with(More)
Error Correcting Output Codes (ECOC) is a popular framework for addressing multi-class classification problems by combing multiple binary sub-problems. In each binary sub-problem, at least one class is actually a " meta-class " consisting of multiple original classes, and treated as a single class in the learning process. This strategy brings a simple and(More)
Ts87 is an immunodominant antigen that induces protective immunity against Trichinella spiralis larval challenge in mice. To determine if a combination of recombinant Ts87 protein and its coding DNA induces a stronger immune response in female C57BL/6 mice were immunized with 100 μg of recombinant Ts87 protein plus its coding DNA cloned in vector pVAX1, or(More)