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Inferring Graphs from Cascades: A Sparse Recovery Framework.

, and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 977-986. JMLR.org, (2015)

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Design and Analysis of Bipartite Experiments Under a Linear Exposure-response Model., , , , and . EC, page 606. ACM, (2022)Inferring Graphs from Cascades: A Sparse Recovery Framework., and . WWW (Companion Volume), page 625-626. ACM, (2015)Modeling Interference Using Experiment Roll-out., , and . EC, page 298. ACM, (2023)Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls., , , , , , , and . NeurIPS, page 8691-8701. (2021)Optimizing Cluster-based Randomized Experiments under Monotonicity., , , and . KDD, page 2090-2099. ACM, (2018)Generative adversarial networks., , , , , , , and . Commun. ACM, 63 (11): 139-144 (2020)Randomized Experimental Design via Geographic Clustering., , , , , and . KDD, page 2745-2753. ACM, (2019)Causal Inference with Differentially Private (Clustered) Outcomes., , and . CoRR, (2023)Causal Estimation of User Learning in Personalized Systems., , , , , and . EC, page 992-1016. ACM, (2023)Detecting Network Effects: Randomizing Over Randomized Experiments., , , , , , and . KDD, page 1027-1035. ACM, (2017)