In this paper, we exploit the problem of inferring images’ semantic concepts from community-contributed images and their associated noisy tags. To infer the concepts more accura...
It is now widely recognized that user interactions with search results can provide substantial relevance information on the documents displayed in the search results. In this pape...
Shihao Ji, Ke Zhou, Ciya Liao, Zhaohui Zheng, Gui-...
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Acquiring knowledge has long been the major bottleneck preventing the rapid spread of AI systems. Manual approaches are slow and costly. Machine-learning approaches have limitatio...