This paper describes an ecient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...
Machine learning and statistical methods have yielded impressive results in a wide variety of natural language processing tasks. These advances have generally been regarded as eng...
The morphology of Semitic languages is unique in the sense that the major word-formation mechanism is an inherently non-concatenative process of interdigitation, whereby two morph...
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments...
In Nearest Rectangle (NR) learning, training instances are generalized into hyperrectangles and a query is classified according to the class of its nearest rectangle. The method ha...