We consider the Bayesian ranking and selection problem, in which one wishes to allocate an information collection budget as efficiently as possible to choose the best among severa...
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
Network intruders try to hide their identity by relaying their traf c through a number of intermediate hosts, called stepping stones. Network ow watermarks have been used to detec...
This paper presents a new approach to estimate “universal” phoneme posterior probabilities for mixed language speech recognition. More specifically, we propose a new theoreti...
Learning for sentence re-writing is a fundamental task in natural language processing and information retrieval. In this paper, we propose a new class of kernel functions, referre...