Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
We study three scheduling problems (file redistribution, independent tasks scheduling and broadcasting) on large scale heterogeneous platforms under the Bounded Multi-port Model. I...
We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BE...
Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinald...
The effects of random variations during the manufacturing process on devices can be simulated as a variation of transistor parameters. Device degradation, due to temperature or vo...
Udo Sobe, Karl-Heinz Rooch, Andreas Ripp, Michael ...