Publications [#356400] of Vincent Conitzer

Conference articles PUBLISHED

1. Conitzer, V; Panigrahi, D; Zhang, H, Learning opinions in social networks, 37th International Conference on Machine Learning, ICML 2020, vol. PartF168147-3 (January, 2020), pp. 2100-2110, ISBN 9781713821120
   (last updated on 2024/07/31)

   Abstract:
   We study the problem of learning opinions in social networks. The learner observes the states of some sample nodes from a social network, and tries to infer the states of other nodes, based on the structure of the network. We show that sample-efficient learning is impossible when the network exhibits strong noise, and give a polynomial-time algorithm for the problem with nearly optimal sample complexity when the network is sufficiently stable.