We propose a new approach to language modeling which utilizes discriminative learning methods. Our approach is an iterative one: starting with an initial language model, in each i...
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...
We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically wellfounded machine learning method to combine a set of...
For software executing several threads in parallel, testing is unreliable, as it cannot cover all thread schedules. Model checking, however, can cover all possible thread interlea...
We present a generative model for the unsupervised learning of dependency structures. We also describe the multiplicative combination of this dependency model with a model of line...