We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
Since TCP can only detect congestion after packet losses have already happened, various forms of Fast TCP (FTCP) have been proposed to notify congestion early and avoid packet los...
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques partic...
We present an automated program analysis, called Reach, to compute program inputs that cause evaluation of explicitly-marked target expressions. Reach has a range of applications ...