We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
This paper presents a data- ow computer, constituted of a large array of data- ow processors and programmed using a functional language, and its application to realtime image proc...
The persistent programming systems of the 1980s offered a programming model that integrated computation and long-term storage. In these systems, reliable applications could be eng...
Alan Dearle, Graham N. C. Kirby, Stuart J. Norcros...
We present an online, recursive filtering technique to model linear dynamical systems that operate on the state space of symmetric positive definite matrices (tensors) that lie on...
Simulation optimization is rapidly becoming a mainstream tool for simulation practitioners. Simulation optimization is the practice of linking an optimization method with a simula...