Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
Abstract. Spector et al. have shown [1],[2],[3] that genetic programming can be used to evolve quantum circuits. In this paper, we present new results in this field, introducing p...
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
We introduce a logic programming framework for data type transformations based on isomorphisms between elementary data types (natural numbers, finite functions, sets and permutat...
We report our experience in implementing type and memory safety in an efficient manner for sensor network nodes running TinyOS: tiny embedded systems running legacy, C-like code. ...
John Regehr, Nathan Cooprider, Will Archer, Eric E...