Abstract— In this paper, we develop methods to “sample” a large real network into a small realistic graph. Although topology modeling has received a lot attention lately, it ...
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithmse.g., clustering, conditioning ar...
We present a simple formulation of Assumption-Commitment reasoning using CSP. In our formulation, an assumption-commitment style property of a process SYS takes the form COM SYS A...
Social network-based Sybil defenses exploit the trust exhibited in social graphs to detect Sybil nodes that disrupt an algorithmic property (i.e., the fast mixing) in these graphs...
Clustering is a central unsupervised learning task with a wide variety of applications. Not surprisingly, there exist many clustering algorithms. However, unlike classification ta...