Accurate network modeling is critical to the design of network protocols. Traditional modeling approaches, such as Discrete Time Markov Chains (DTMC) are limited in their ability ...
We introduce the probabilistic class SBP which is defined in a BPP-like manner. This class emerges from BPP by keeping the promise of a probability gap but decreasing the probabil...
In an open networking environment, a workstation usually needs to identify its legal users for providing its services. Kerberos provides an efficient approach whereby a trusted th...
Resolving an issue open since Fenner, Fortnow, and Kurtz raised it in [FFK94], we prove that LWPP is not uniformly gap-definable and that WPP is not uniformly gap-definable. We do...
This paper studies sequence prediction based on the monotone Kolmogorov complexity Km=-log m, i.e. based on universal deterministic/one-part MDL. m is extremely close to Solomonof...