Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...
We study online job scheduling on a processor that can vary its speed dynamically to manage its power. We attempt to extend the recent success in analyzing total unweighted flow ti...
Multiobjective optimization deals with problems involving multiple measures of performance that should be optimized simultaneously. In this paper we extend bucket elimination (BE),...
This paper analyses the micro-threaded model of concurrency making comparisons with both data and instruction-level concurrency. The model is fine grain and provides synchronisati...
Deterministic annealing and relaxation labeling algorithms for classification and matching are presented and discussed. A new approach--self annealing--is introduced to bring dete...