We describe a slightly subexponential time algorithm for learning parity functions in the presence of random classification noise, a problem closely related to several cryptograph...
This paper addresses the problem of allocating (assigning and scheduling) periodic task modules to processing nodes in distributed real-time systems subject to task precedence and ...
Abstract-- Efficient detection of globally optimal surfaces representing object boundaries in volumetric datasets is important and remains challenging in many medical image analysi...
In the geometric data model [6], spatio-temporal data are modelled as a finite collection of triangles that are transformed by time-dependent affinities. To facilitate querying an...
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...