We present a novel approach for learning patterns (sub-images) shared by multiple images without prior knowledge about the number and the positions of the patterns in the images. ...
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspe...
The problems of providing a real, physical specialist laboratory to teach computer networking such as, the lack of funding and physical space and the risks and threats to the netw...
– Probabilistic Inference Networks are becoming increasingly popular for modeling and reasoning in uncertain domains. In the past few years, many efforts have been made in learni...