We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
This paper1 presents an empirical approach to mining parallel corpora. Conventional approaches use a readily available collection of comparable, nonparallel corpora to extract par...
We present an online learning algorithm for training parsers which allows for the inclusion of multiple objective functions. The primary example is the extension of a standard sup...
Keith Hall, Ryan T. McDonald, Jason Katz-Brown, Mi...
A novel automatic image annotation system is proposed, which integrates two sets of SVMs (Support Vector Machines), namely the MIL-based (Multiple Instance Learning) and global-fe...
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...