Statistics and Machine Learning
Submitted Papers
Cho, J., Kim, D., Rohe, K., Wang, S. (2019). The Operating Principle of Regularized Spectral Clustering. Submitted.
Published/Accepted Papers
Han, S., Kim, D., and Kim, H. (2023+). Adaptive Thresholding for Iterative Matrix Completion with Heterogeneous Missing Probability: H-AdaptiveImpute. To be appeared in Communications in Statistics - Simulation and Computation.
Cho. J., Kim, D., and Rohe, K. (2019). Intelligent Initialization and Adaptive Thresholding for Iterative Matrix Completion; Some Statistical and Algorithmic Theory for Adaptive-Impute. Journal of Computational and Graphical Statistics, 28, 323-333. pdf file.
Cho, J., Kim, D., and Rohe, K. (2017). Asymptotic Theory for Estimating the Singular Vectors and Values of a Partially-observed Low Rank Matrix with Noise. Statistica Sinica, 27, 1921-1948. pdf.
Kim, D. and Zhang, C. (2014). Adaptive Linear Step-up Multiple Testing Procedure with the Bias-Reduced Estimator. Statistics and Probability Letters, 87, 31-39.