From an empirical point of view, the hardness of quantified Boolean formulas (QBFs), can be characterized by the (in)ability of current state-of-the-art QBF solvers to decide abo...
In this report we address the problem of static scheduling of realtime systems that include both hard and soft tasks. We consider systems in which both hard and soft tasks are per...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Applications written in unsafe languages like C and C++ are vulnerable to memory errors such as buffer overflows, dangling pointers, and reads of uninitialized data. Such errors ...
Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in...