The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measuremen...
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time length...
Constant propagation (CP) is one of the most widely used optimizations in practice (cf. [9]). Intuitively, it addresses the problem of statically detecting whether an expression al...
We consider the problem of processing a given number of tasks on a given number of processors as quickly as possible when only vague information about the processing time of a task...
In recent years, existing computing schemes and paradigms have evolved towards more flexible, ad-hoc scalable frameworks. Nowadays, exchanging interactions between entities often ...