Optimal high-dimensional and nonparametric distributed testing under communication constraints

Author:

Szabó Botond1,Vuursteen Lasse2,van Zanten Harry3

Affiliation:

1. Department of Decision Sciences, Bocconi Institute for Data Science and Analytics (BIDSA), Bocconi University

2. Delft Institute of Applied Mathematics (DIAM), Delft University of Technology

3. Department of Mathematics, Vrije Universiteit Amsterdam

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference38 articles.

1. ACHARYA, J., CANONNE, C. L. and TYAGI, H. (2020). Inference under information constraints I: Lower bounds from chi-square contraction. IEEE Trans. Inf. Theory 66 7835–7855.

2. ACHARYA, J., CANONNE, C. L. and TYAGI, H. (2020). Inference under information constraints II: Communication constraints and shared randomness. IEEE Trans. Inf. Theory 66 7856–7877.

3. ACHARYA, J., CANONNE, C. L. and TYAGI, H. (2020). Distributed signal detection under communication constraints. In Proceedings of Thirty Third Conference on Learning Theory (J. Abernethy and S. Agarwal, eds.). Proceedings of Machine Learning Research 125 41–63. PMLR.

4. AHLSWEDE, R. and CSISZÁR, I. (1986). Hypothesis testing with communication constraints. IEEE Trans. Inf. Theory 32 533–542.

5. BARNES, L. P., HAN, Y. and ÖZGÜR, A. (2020). Lower bounds for learning distributions under communication constraints via Fisher information. J. Mach. Learn. Res. 21 Paper No. 236, 30.

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