Machine learning and data mining have become aware that using constraints when learning patterns and rules can be very useful. To this end, a large number of special purpose syste...
We present a framework that we are developing to better solve several critical issues that arise when interactive systems are extended to large displays. These issues include slow...
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
We investigate a new approach for solving boundary control problems for dynamical systems that are governed by transport equations, when the control function is restricted to binar...
We present optimal solutions to the test scheduling problem for core-based systems. We show that test scheduling is equivalent to the m-processor open-shop scheduling problem and ...