Causal Influence in Federated Edge Inference

arXiv:2405.01260v1 Announce Type: new
Abstract: In this paper, we consider a setting where heterogeneous agents with connectivity are performing inference using unlabeled streaming data. Observed data are only partially informative about the target variable of interest. In order to overcome the uncertainty, agents cooperate with each other by exchanging their local inferences with and through a fusion center. To evaluate how each agent influences the overall decision, we adopt a causal framework in order to distinguish the actual influence of …

abstract agents arxiv causal connectivity cs.lg cs.ma cs.sy data edge eess.sp eess.sy inference inferences influence paper streaming streaming data type uncertainty