Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on the signal frequency. As a consequence, transmission...
Daniel Enrique Lucani, Milica Stojanovic, Muriel M...
We investigate the decidability of observational equivalence and approximation in Reynolds' "Syntactic Control of Interference" (SCI), a prototypical functionalimpe...
The application of the wavelet transform in image processing is most frequently based on a separable transform. Lines and columns in an image are treated independently and the bas...
Pier Luigi Dragotti, Vladan Velisavljevic, Martin ...