Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
We study the problem of learning using combinations of machines. In particular we present new theoretical bounds on the generalization performance of voting ensembles of kernel ma...
We propose measuring "visualness" of concepts with images on the Web, that is, what extent concepts have visual characteristics. This is a new application of "Web i...
Parallel software is increasingly necessary to take advantage of multi-core architectures, but it is also prone to concurrency bugs which are particularly hard to avoid, find, an...
Detecting errors in an early phase of software development can help to reduce the cost of software systems. Many research attempts presented a fixed set of rules to help finding e...