540 citations · 1.1k across the 26 of their papers we have counts for
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3 papers · 1 filter
math.ST2018
Reducing Seed Bias in Respondent-Driven Sampling by Estimating Block Transition Probabilities
Yilin Zhang, Karl Rohe, Sebastien Roch
Respondent-driven sampling (RDS) is a popular approach to study marginalized or hard-to-reach populations. It collects samples from a networked population by incentivizing particip…
math.ST2018★ 1 cited
Asymptotic Seed Bias in Respondent-driven Sampling
Yuling Yan, Bret Hanlon, Sebastien Roch +1
Respondent-driven sampling (RDS) collects a sample of individuals in a networked population by incentivizing the sampled individuals to refer their contacts into the sample. This i…
stat.ML2018★ 50 cited
Understanding Regularized Spectral Clustering via Graph Conductance
Yilin Zhang, Karl Rohe
This paper uses the relationship between graph conductance and spectral clustering to study (i) the failures of spectral clustering and (ii) the benefits of regularization. The exp…