289 citations · 400 across the 9 of their papers we have counts for
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cs.SI2016★ 19 cited
Learning Influence Functions from Incomplete Observations
Xinran He, Ke Xu, David Kempe +1
We study the problem of learning influence functions under incomplete observations of node activations. Incomplete observations are a major concern as most (online and real-world)…
cs.SI2016★ 10 cited
Robust Influence Maximization
Xinran He, David Kempe
Uncertainty about models and data is ubiquitous in the computational social sciences, and it creates a need for robust social network algorithms, which can simultaneously provide g…