AR-sieve Bootstrap for High-dimensional Time Series
Bi, D., Shang, H. L., Yang, Y., & Zhu, H. (2021). AR-sieve Bootstrap for High-dimensional Time Series. arXiv preprint arXiv:2112.00414.
CV
Education
- Bachelor of Economics: Major in Finance, Minor in Statistics, Xiamen University, 2013
- Master of Actuarial Studies, The Australian National University, 2015
- Ph.D in Statistics, The Australian National University, 2021
Work experience
- 2021~now: Assistant Professor at Hunan University
- 2020~2021: Associate Lecturer at The Australian National University
Research projects
PI: National Science Foundation of China, 72201093, ‘Forecasting and inference for high-dimensional time series’, 2023.01-2025.12
Publications and preprints
Spiked eigenvalues of high-dimensional sample autocovariance matrices: CLT and applications
Bi, D., Han, X., Nie, A., & Yang, Y. (2022). Spiked eigenvalues of high-dimensional sample autocovariance matrices: CLT and applications. arXiv preprint arXiv:2201.03181.
Homogeneity and Sub-homogeneity Pursuit: Iterative Complement Clustering PCA
Bi, D., Chang, L., & Yang, Y. (2022). Homogeneity and Sub-homogeneity Pursuit: Iterative Complement Clustering PCA. arXiv preprint arXiv:2203.06573.
Feddip: Federated learning with extreme dynamic pruning and incremental regularization
Long, Q., Anagnostopoulos, C., Parambath, S. P., & Bi, D. (2023). Feddip: Federated learning with extreme dynamic pruning and incremental regularization. In 2023 IEEE International Conference on Data Mining (ICDM) (pp. 1187-1192).
Decentralized Personalized Federated Learning Based on a Conditional “Sparse-to-Sparser” Scheme
Long, Q., Wang, Q., Anagnostopoulos, C., & Bi, D. (2025). Decentralized Personalized Federated Learning Based on a Conditional "Sparse-to-Sparser" Scheme. IEEE Transactions on Neural Networks and Learning Systems.