PUBLICATIONS

Reinforcement learning:

R. Zhou, T. Liu, M. Cheng, D. Kalathil, P. R. Kumar, and C. Tian, “Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation,” Neurips 2023.

R. Zhou, T. Liu, D, Kalathil. P.R., Kumar, and C. Tian, “Anchor-changing regularized natural policy gradient for multi-objective reinforcement learning,” Neurips 2022.

T. Liu, R. Zhou, D, Kalathil. P.R., Kumar, and C. Tian, “Learning policies with zero or bounded constraint violation for constrained MDPs,” Neurips 2021.

Generalization Error:

R. Zhou, C. Tian, T. Liu “Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem,” ISIT 2023.

R. Zhou, C. Tian, and T. Liu, “Individually conditional individual mutual information bound on generalization error,” IEEE Transactions on Information Theory, 68(5), pp. 3304-3316, Jan. 2022.

R. Zhou, C. Tian, and T. Liu, “Stochastic Chaining and Strengthened Information-Theoretic Generalization Bounds,” ISIT 2022.

Information-theoretic Private Information Retrieval:

R. Zhou, C. Tian, H. Sun, and J. S. Plank, "Two-level private information retrieval," IEEE Journal on Selected Areas in Information Theory, Jun. 2022.

R. Zhou, C. Tian, H. Sun, and T. Liu, (2020). “Capacity-achieving private information retrieval codes from MDS-coded databases with minimum message size,” IEEE Transactions on Information Theory, 66(8), pp. 4904-4916, Feb. 2020. (2020-2021 IEEE Data Storage Best Student Paper Award) 

1. R. Zhou, C. Tian, and T. Liu, “Stochastic chaining and strengthened information-theoretic generalization bounds,” Journal of the Franklin Institute, Feb. 2023

2. R. Zhou, C. Tian, H. Sun, and J. S. Plank, "Two-level private information retrieval," IEEE Journal on Selected Areas in Information Theory, Jun. 2022.

3. W. Chen, R. Zhou, C. Tian, and C. Shen, “On top-k selection from m-wise partial rankings via Borda counting,” IEEE Transactions on Signal Processing, 70, pp. 2031 - 2045, Apr. 2022.

4. R. Zhou, C. Tian, and T. Liu, “Individually conditional individual mutual information bound on generalization error,” IEEE Transactions on Information Theory, 68(5), pp. 3304-3316, Jan. 2022.

5. C. Tian, J. Plank, B. Hurst, and R. Zhou, “Computational techniques for investigating information-theoretic limits of information systems,” Information, 12(2), 82, Feb. 2021.

6. T. Guo, R. Zhou, and C. Tian, “New results on the storage-retrieval tradeoff in private information retrieval systems,” IEEE Journal on Selected Areas in Information Theory, 2(1), pp. 403-414, Jan. 2021.

7. C. Wang, J. Yang, H. He, R. Zhou, S. Chen, and X. Jiang, “Neighbor cell list optimization in handover management using cascading bandits algorithm,” IEEE Access, 8, 134137-134150, Jul. 2020.

8. C. Gan, R. Zhou, J. Yang, and C. Shen, “Cost-aware cascading bandits,” IEEE Transactions on Signal Processing, 68, pp. 3692-3706, Jun. 2020.

9. T. Guo, R. Zhou, and C. Tian, "On the information leakage in private information retrieval systems," IEEE Transactions on Information Forensics and Security, 15, pp. 2999-3012, Mar. 2020.

10. R. Zhou, C. Tian, H. Sun, and T. Liu, (2020). “Capacity-achieving private information retrieval codes from MDS-coded databases with minimum message size,” IEEE Transactions on Information Theory, 66(8), pp. 4904-4916, Feb. 2020.

11. C. Gan, R. Zhou, J. Yang, and C. Shen, “Cost-aware learning and optimization for opportunistic spectrum access,” IEEE Transactions on Cognitive Communications and Networking, 5(1), pp. 15-27, Dec. 2018

12. Z. Wang, R. Zhou, and C. Shen, "Regional multi-armed bandits with partial informativeness," IEEE Transactions on Signal Process, 66(21), pp. 5705-5717, Nov. 2018

13. C. Shen, R. Zhou, C. Tekin, and M. van der Schaar, “Generalized global bandit and its application in cellular coverage optimization,” IEEE Journal of Selected Topics in Signal Processing, 12(1), pp. 218-232, Jan. 2018.

1. R. Zhou, T. Liu, M. Cheng, D. Kalathil, P. R. Kumar, and C. Tian, “Natural Actor-Critic for Robust Reinforcement Learning with Function Approximation,” 2023 Conference on Neural Information Processing Systems (Neurips), Nov. 2023. (acceptance rate 26.1%)

2. L. Fan, R. Zhou, C. Tian, and C. Shen, “Federated Linear Bandits with Finite Adversarial Actions,” 2023 Conference on Neural Information Processing Systems (Neurips), Nov. 2023. (acceptance rate 26.1%)

3. Y. Sun, T. Liu, R. Zhou, P. R. Kumar, and S. Shahrampour, “Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games,” 2023 Conference on Neural Information Processing Systems (Neurips), Nov. 2023. (acceptance rate 26.1%)

4. R. Zhou, C. Tian, T. Liu “Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem,” In proceedings of 2022 IEEE International Symposium on Information Theory (ISIT), Jul. 2023.

5. R. Zhou, T. Liu, D, Kalathil. P.R., Kumar, and C. Tian, “Anchor-changing regularized natural policy gradient for multi-objective reinforcement learning,” 2022 Conference on Neural Information Processing Systems (Neurips) Sep. 2021. (acceptance rate 25.6%)

6. T. Liu, P. R. Kumar, R. Zhou, and X. Liu, “Learning from small samples: transformation-invariant SVMs with composition and locality at multiple scales,” 2022 Conference on Neural Information Processing Systems (Neurips) Sep. 2021. (acceptance rate 25.6%)

7. R. Zhou, C. Tian, and T. Liu, “Stochastic chaining and strengthened information-theoretic generalization bounds,” In proceedings of 2021 IEEE International Symposium on Information Theory (ISIT), Jun. 2022.

8. C. Qian, R. Zhou, and C. Tian, “Improved weakly private information retrieval codes,” In proceedings of 2021 IEEE International Symposium on Information Theory (ISIT), Jun. 2022. 

9. R. Zhou, and C. Tian, “Approximate top-m arm identification with heterogeneous reward variances,” 2022 International Conference on Artificial Intelligence and Statistics (AISTATS) PMLR pp. 7483-7504, May. 2021. (acceptance rate 29%)

10. T. Liu, R. Zhou, D, Kalathil. P.R., Kumar, and C. Tian, “Learning policies with zero or bounded constraint violation for constrained MDPs,” 2021 Conference on Neural Information Processing Systems (Neurips) Aug. 2021. (acceptance rate 26%)

11. R. Zhou, C. Tian, and T. Liu, “Individually conditional individual mutual information bound on generalization error,” In proceedings of 2021 IEEE International Symposium on Information Theory (ISIT) pp. 670-675, Jul. 2021.

12. R. Zhou, C. Tian, H. Sun, S.J. Plank, “Two-level private information retrieval,” In proceedings of 2021 IEEE International Symposium on Information Theory (ISIT) pp. 1919-1924, Jul. 2021.

13. R. Zhou, T. Guo, and C. Tian, “Weakly private information retrieval under the maximal leakage metric,” In proceedings of 2020 IEEE International Symposium on Information Theory (ISIT) pp. 1089-1094, Jun. 2020.

14. W. Chen, R. Zhou, C. Tian, and C. Shen, “On top-k selection from m-wise partial rankings via Borda counting,” In proceedings of 2020 IEEE International Symposium on Information Theory (ISIT) pp. 2759-2764, Jun. 2020.

15. C. Wang, R. Zhou, J. Yang, and C. Shen, “A cascading bandit approach to efficient mobility management in ultra-dense networks,” In proceedings of 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing (MLSP) pp. 1-6, Oct. 2019.

16. R. Zhou, C. Tian, H. Sun, and T. Liu, “Capacity-achieving private information retrieval codes from MDS-coded databases with minimum message size,” In proceedings of 2019 IEEE International Symposium on Information Theory (ISIT) pp. 370-374, Jul. 2019.

17. C. Gan, J. Yang, R. Zhou, and C. Shen, “Online learning with diverse user preferences,” In proceedings of 2019 IEEE International Symposium on Information Theory (ISIT) pp. 2539-2543, Jul. 2019.

18. R. Zhou, C. Gan, J. Yang, and C. Shen, “Cost-aware cascading bandits,” In Proceedings of 27th International Joint Conference on Artificial Intelligence (IJCAI) pp. 3228-3234, Jul. 2018. (acceptance rate 20.5%)

19. Z. Wang, R. Zhou, and C. Shen, "Regional multi-armed bandits," In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 84:510- 518, Playa Blanca, Lanzarote, Canary Islands, Apr. 2018.