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...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
We present a decomposition-based approach to managing probabilistic information. We introduce world-set decompositions (WSDs), a space-efficient and complete representation system ...
Abstract. Propositional dynamic logic (PDL) provides a natural setting for semantics of means-end relations involving non-determinism, but such models do not include probabilistic ...
Jesse Hughes, Albert C. Esterline, Bahram Kimiagha...
We present a consensus algorithm that combines unreliable failure detection and randomization, two well-known techniques for solving consensus in asynchronous systems with crash f...