In this paper, we present an approach to the automatic identification and correction of preposition and determiner errors in nonnative (L2) English writing. We show that models of...
This paper investigates the correlation between acoustic confidence scores as returned by speech recognizers with recognition quality. We report the results of two machine learni...
We present a new approach for mapping natural language sentences to their formal meaning representations using stringkernel-based classifiers. Our system learns these classifiers ...
This paper describes an empirical study to investigate the performance of a wide range of classifiers deployed in applications to classify biometric data. The study specifically re...
We define notions of stability for learning algorithms and show how to use these notions to derive generalization error bounds based on the empirical error and the leave-one-out e...