Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
We consider information-theoretic key agreement between two parties sharing somewhat different versions of a secret w that has relatively little entropy. Such key agreement, also ...
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...
We present a mathematical model for the problem of scheduling tests for core-based system-on-chip (SOC) VLSI designs. Given a set of tests for each core in the SOC and a set of te...
We present a generic aproach to the static analysis of concurrent programs with procedures. We model programs as communicating pushdown systems. It is known that typical dataflow ...