Inference Under Information Constraints II: Communication Constraints and Shared Randomness

@article{Acharya2020InferenceUI,
  title={Inference Under Information Constraints II: Communication Constraints and Shared Randomness},
  author={Jayadev Acharya and Cl{\'e}ment L. Canonne and Himanshu Tyagi},
  journal={IEEE Transactions on Information Theory},
  year={2020},
  volume={66},
  pages={7856-7877}
}
A central server needs to perform statistical inference based on samples that are distributed over multiple users who can each send a message of limited length to the center. We study problems of distribution learning and identity testing in this distributed inference setting and examine the role of shared randomness as a resource. We propose a general-purpose simulate-and-infer strategy that uses only private-coin communication protocols and is sample-optimal for distribution learning. This… Expand
Communication-Constrained Inference and the Role of Shared Randomness
Inference Under Information Constraints III: Local Privacy Constraints
Distributed Signal Detection under Communication Constraints
Inference Under Information Constraints I: Lower Bounds From Chi-Square Contraction
Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints
Communication Complexity of Distributed High Dimensional Correlation Testing
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