State estimation in multiagent settings involves updating an agent’s belief over the physical states and the space of other agents’ models. Performance of the previous approac...
While a lot of progress has been made in improving analyses and tools that aid software development, less effort has been spent on studying how such tools are commonly used in pra...
This paper treats nominal entity tagging as a six-way (five categories plus nonentity) classification problem and applies a smoothing maximum entropy (ME) model with a Gaussian pr...
In this paper we examine how the differences in modelling between different data driven systems performing the same NLP task can be exploited to yield a higher accuracy than the b...
Graph partitioning algorithms play a central role in data analysis and machine learning. Most useful graph partitioning criteria correspond to optimizing a ratio between the cut a...