With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Most modern compilers operate by applying a fixed, program-independent sequence of optimizations to all programs. Compiler writers choose a single “compilation sequence”, or ...
L. Almagor, Keith D. Cooper, Alexander Grosul, Tim...
We explore the revenue capabilities of truthful, monotone (“fair”) allocation and pricing functions for resource-constrained auction mechanisms within a general framework that ...
This paper explores the application of multiobjective Genetic Algorithms (mGAs) to rural land use planning, a spatial allocation problem. Two mGAs are proposed. Both share an unde...
Keith B. Matthews, Susan Craw, Stewart Elder, Alan...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...