Xiyang Hu
Ph.D. Student at Carnegie Mellon University
Xiyang Hu is a Ph.D. student at Carnegie Mellon University. His research focuses on: 1. the design of Machine Learning models to facilitate decision-making in various application domains; and 2. the understanding of the social impacts of AI and digital platforms.
He got his M.Sc. in Statistical Science from Duke University, and B.Arch. in Architecture with a minor in Computer Science and Technology from Tsinghua University.
Publications
Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu (2020). COPOD: Copula-Based Outlier Detection. IEEE International Conference on Data Mining (ICDM).
Xiyang Hu, Cynthia Rudin, Margo Seltzer (2019). Optimal sparse decision trees. In Advances in Neural Information Processing Systems (NeurIPS).
Additional Information