In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
In this paper we analyze the PAC learning abilities of several simple iterative algorithms for learning linear threshold functions, obtaining both positive and negative results. W...
— This paper presents an algorithm for adapting periodic behavior to gradual shifts in task parameters. Since learning optimal control in high dimensional domains is subject to t...
This paper presents a solution to the open problem of finding the optimal tile size to minimise the execution time of a parallelogram-shaped iteration space on a distributed memory...
A well-studied problem in the electric power industry is that of optimally scheduling preventative maintenance of power generating units within a power plant. We show how these pr...