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Proofs and Insights into Causal Clustering Experiments under Network Interference by@escholar

Proofs and Insights into Causal Clustering Experiments under Network Interference

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The paper investigates the optimal design of clustering in experimental setups, particularly in the context of social networks. It discusses theoretical frameworks, objective functions, and practical algorithms for choosing the best clustering method. The authors analyze the impact of various factors, including bias, variance, and spillover effects, providing recommendations for real-world applications.
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EScholar: Electronic Academic Papers for Scholars HackerNoon profile picture
EScholar: Electronic Academic Papers for Scholars

EScholar: Electronic Academic Papers for Scholars

@escholar

We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community

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EScholar: Electronic Academic Papers for Scholars HackerNoon profile picture
EScholar: Electronic Academic Papers for Scholars@escholar
We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community

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