In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Supervised learners can be used to automatically classify many types of spatially distributed data. For example, land cover classification by hyperspectral image data analysis is ...
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
With the increasing complexity of large-scale distributed (LSD) systems, an efficient monitoring mechanism has become an essential service for improving the performance and reliab...
Ehab S. Al-Shaer, Hussein M. Abdel-Wahab, Kurt Mal...