This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
We describe an approach to training a statistical parser from a bracketed corpus, and demonstrate its use in a software testing application that translates English speci cations i...
Automating the construction of semantic grammars is a di cult and interesting problem for machine learning. This paper shows how the semantic-grammar acquisition problem can be vi...
We propose an approach to transformational planning and learning of everyday activity. This approach is targeted at autonomous robots that are to perform complex activities such a...