Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Risk assessment in regions with low earthquake activity is important for reinsurance companies and governmental building authorities. They need a complete picture of the possible ...
We present a new general upper bound on the number of examples required to estimate all of the expectations of a set of random variables uniformly well. The quality of the estimat...
As data volumes rise and retention periods increase, the appearance of "better, faster and cheaper" storage infrastructure seems like an all-encompassing solution to con...
In distributed admission control (AC) schemes, handling concurrent AC decisions assumes a relevant role in avoiding over or false acceptance and, consequently, service quality degr...