We describe a general approach to optimization which we term Squeaky Wheel" Optimization SWO. In SWO, a greedy algorithm is used to construct a solution which is then analyze...
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Despite years of work on retargetable compilers, creating a good, reliable back end for an optimizing compiler still entails a lot of hard work. Moreover, a critical component of ...
This paper introduces improvements in partitioning schemes for multiprocessor real-time systems which allow higher processor utilization and enhanced schedulability by using exact...
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...