We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
— We consider energy efficient network coding design in wireless networks with multiple unicast sessions. Our approach decomposes multiple unicast sessions into a superposition ...
Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverag...
Onur Guzey, Li-C. Wang, Jeremy R. Levitt, Harry Fo...
Interactive steering with visualization has been a common goal of the visualization research community for twenty years, but it is rarely ever realized in practice. In this paper w...
Kresimir Matkovic, Denis Gracanin, Mario Jelovic, ...
—In this paper we propose and evaluate an overlay distribution algorithm for P2P, chunk-based, streaming systems over forest-based topologies. In such systems, the stream is divi...
Giuseppe Bianchi, Nicola Blefari-Melazzi, Lorenzo ...