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Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention's effects and which subpopulations to explicitly estimate.
Graph Structure Learning from Unlabeled Data for Event Detection
Processes such as disease propagation and information diffusion often spread over some latent network structure which must be learned from observation.
Distribution Shift in Airline Customer Behavior during COVID-19
Traditional AI approaches in customized (personalized) contextual pricing applications assume that the data distribution at the time of online pricing is similar to that observed during training.
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