Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
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...
—Segmentation, the task of splitting a long sequence of discrete symbols into chunks, can provide important information about the nature of the sequence that is understandable to...
Seed sampling is critical in semi-supervised learning. This paper proposes a clusteringbased stratified seed sampling approach to semi-supervised learning. First, various clusteri...