We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the ca...
The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive preprocessing to bridge the representation ga...
The cerebellum plays a major role in motor control. It is thought to mediate the acquisition of forward and inverse internal models of the bodyenvironment interaction [1]. In this ...
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...