Bumptrees for Efficient Function, Constraint and Classification Learning

Neural Information Processing Systems 

A new class of data structures called "bumptrees" is described. These structures are useful for efficiently implementing a number of neural network related operations. An empirical comparison with radial basis functions is presented on a robot ann mapping learning task. A bumptree is a new geometric data structure which is useful for efficiently learning. They are a natural generalization of several hierarchical geometric data structures including oct-trees.