We propose a novel method, based on concepts from expander graphs, to sample communities in networks. We show that our sampling method, unlike previous techniques, produces subgra...
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
We consider the problem of learning a coefficient vector x0 ∈ RN from noisy linear observation y = Ax0 + w ∈ Rn . In many contexts (ranging from model selection to image proce...
In crowdsourced relevance judging, each crowd worker typically judges only a small number of examples, yielding a sparse and imbalanced set of judgments in which relatively few wo...
Malware categorization is an important problem in malware analysis and has attracted a lot of attention of computer security researchers and anti-malware industry recently. Todayâ...