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Xiyang Hu

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 DetectionIEEE 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