Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
Solomonoff unified Occam’s razor and Epicurus’ principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field...
The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to impr...
The ability to detect object size, location and movement is essential for a visual system in either a biological or man made environment. In this paper we present a model for esti...
In order to enable communication between a dynamic collection of peers with given ID’s, such as “machine.cs.school.edu”, over the Internet, a distributed name service must b...