In this paper, we present a new rule induction algorithm for machine learning in medical diagnosis. Medical datasets, as many other real-world datasets, exhibit an imbalanced clas...
Recently, a number of graph partitioning applications have emerged with additional requirements that the traditional graph partitioning model alone cannot e ectively handle. One s...
Large–scale parallel applications performing global synchronization may spend a significant amount of execution time waiting for the completion of a barrier operation. Conseque...
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...