[4] Jayadev Acharya, Clément L. Canonne, Cody Freitag, Ziteng Sun, and Himanshu Tyagi. Inference under information constraints III: local privacy constraints. IEEE J. Sel. Areas Inf. Theory, 2(1):253-267, 2021.
[5] Jayadev Acharya, Clément L. Canonne, Yuhan Liu, Ziteng Sun, and Himanshu Tyagi. Interactive inference under information constraints. IEEE Trans. Inform. Theory, 68(1):502-516, 2022. ISSN 0018-9448. doi: 10.1109/tit.2021.3123905. URL https://doi.org/10.1109/tit. 2021.3123905.
[6] Ziv Bar-Yossef, T. S. Jayram, Ravi Kumar, and D. Sivakumar. An information statistics approach to data stream and communication complexity. J. Comput. System Sci., 68(4):702-732, 2004. ISSN 0022-0000. doi: 10.1016/j.jcss.2003.11.006. URL https://doi.org/10.1016/j.jcss.2003.11.006.
[7] Leighton P. Barnes, Yanjun Han, and Ayfer Özgür. Fisher information for distributed estimation under a blackboard communication protocol. In ISIT, pages 2704-2708. IEEE, 2019.
[8] Leighton Pate Barnes, Wei-Ning Chen, and Ayfer Özgür. Fisher information under local differential privacy. IEEE J. Sel. Areas Inf. Theory, 1(3):645-659, 2020.
[9] Stéphane Boucheron, Gábor Lugosi, and Pascal Massart. Concentration Inequalities: A Nonasymptotic Theory of Independence. OUP Oxford, 2013.
[10] Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, and David P. Woodruff. Communication lower bounds for statistical estimation problems via a distributed data processing inequality. In Symposium on Theory of Computing Conference, STOC'16, pages 1011-1020. ACM, 2016.
[11] Clément L. Canonne, Gautam Kamath, Audra McMillan, Jonathan Ullman, and Lydia Zakynthinou. Private identity testing for high-dimensional distributions. In Advances in Neural Information Processing Systems 33, 2020. To appear. Preprint available at arXiv:abs/1905.11947.
[12] Thomas M. Cover and Joy A. Thomas. Elements of information theory. Wiley-Interscience [John Wiley & Sons], Hoboken, NJ, second edition, 2006. ISBN 978-0-471-24195-9; 0-471-24195-4.
[13] John Duchi and Ryan Rogers. Lower bounds for locally private estimation via communication complexity. In Alina Beygelzimer and Daniel Hsu, editors, Proceedings of the Thirty-Second Conference on Learning Theory, volume 99 of Proceedings of Machine Learning Research, pages 1161–1191, Phoenix, USA, June 2019. PMLR.
[14] John C. Duchi, Michael I. Jordan, and Martin J. Wainwright. Minimax optimal procedures for locally private estimation. J. Amer. Statist. Assoc., 113(521):182-201, 2018. ISSN 0162-1459.
[15] Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. Calibrating noise to sensitivity in private data analysis. In Theory of cryptography, volume 3876 of Lecture Notes in Comput. Sci., pages 265-284. Springer, Berlin, 2006.
[16] Alexandre V. Evfimievski, Johannes Gehrke, and Ramakrishnan Srikant. Limiting privacy breaches in privacy preserving data mining. In PODS, pages 211-222. ACM, 2003.
[17] Ankit Garg, Tengyu Ma, and Huy L. Nguyen. On communication cost of distributed statistical estimation and dimensionality. In Advances in Neural Information Processing Systems 27, pages 2726-2734, 2014.
[18] Yanjun Han, Pritam Mukherjee, Ayfer Özgür, and Tsachy Weissman. Distributed statistical estimation of high-dimensional and non-parametric distributions. In Proceedings of the 2018 IEEE International Symposium on Information Theory (ISIT'18), pages 506-510, 2018.
[19] Yanjun Han, Ayfer Özgür, and Tsachy Weissman. Geometric lower bounds for distributed parameter estimation under communication constraints. In Proceedings of the 31st Conference on Learning Theory, COLT 2018, volume 75 of Proceedings of Machine Learning Research, pages 3163-3188. PMLR, 2018.