Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
Research on resource-bounded agents has established that rational agents need to be able to revise their commitments in the light of new opportunities. In the context of collabora...
We present a new image coding scheme based on an unification of fractal and transform coding. We introduce a generalization of the luminance transformation used by fractal coding ...
In this paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the generalized likeli...
We present a methodology for the real time alignment of music signals using sequential Montecarlo inference techniques. The alignment problem is formulated as the state tracking o...