Mai, X., & Liao, Z. (2020). High dimensional classification via regularized and unregularized empirical risk minimization: precise error and optimal loss.
Mai, X., & Couillet, R. (2021). Consistent semi-supervised graph regularization for high dimensional data. The Journal of Machine Learning Research, 22(94), 1–48.
Mai, X., & Couillet, R. (2018). A random matrix analysis and improvement of semi-supervised learning for large dimensional data. The Journal of Machine Learning Research, 19(1), 3074–3100.
Mai, X., Avestimehr, S., Ortega, A., & Soltanolkotabi, M. (2022). On the effectiveness of active learning by uncertainty sampling in classification of Gaussian mixture data. (Accepted) 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Mai, X., Liao, Z., & Couillet, R. (2019). A large scale analysis of logistic regression: Asymptotic performance and new insights. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3357–3361.
Mai, X., & Couillet, R. (2019). Revisiting and improving semi-supervised learning: a large dimensional approach. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3547–3551.
Couillet, R., Liao, Z., & Mai, X. (2018). Classification asymptotics in the random matrix regime. 2018 26th European Signal Processing Conference (EUSIPCO), 1875–1879.
Mai, X., & Couillet, R. (2017). The counterintuitive mechanism of graph-based semi-supervised learning in the big data regime. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2821–2825.
