Xiyang Hu
Ph.D. at Carnegie Mellon University
Xiyang Hu is a Ph.D. student at Carnegie Mellon University. His research focuses on machine learning, deep learning, and information systems.
Specifically, he works on:
- The design of Machine Learning models to facilitate decision-making in various domains.
- The understanding of the social impacts of AI and responsible Human-AI interaction.
He got his M.Sc. in Statistical Science from Duke University, and B.Arch. in Architecture with a minor in Computer Science from Tsinghua University.
Publications
Xiyang Hu, Xinchi Chen, Peng Qi, Deguang Kong, Kunlun Liu, William Yang Wang, Zhiheng Huang (2023). Language Agnostic Multilingual Information Retrieval with Contrastive Learning. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL).
Xiyang Hu, Yan Huang, Beibei Li, Tian Lu (2022). Credit Risk Modeling without Sensitive Features: An Adversarial Deep Learning Model for Fairness and Profit. Proceedings of International Conference on Information Systems (ICIS).
Songqiao Han*, Xiyang Hu*, Hailiang Huang*, Mingqi Jiang*, and Yue Zhao* (2022). ADBench: Anomaly Detection Benchmark. In Advances in Neural Information Processing Systems (NeurIPS).
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, et al (2022). Benchmarking Node Outlier Detection on Graphs. In Advances in Neural Information Processing Systems (NeurIPS).
Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, et al (2022). PyGOD: A Python Library for Graph Outlier Detection. arXiv preprint arXiv:2204.12095.
Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen (2022). ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. IEEE Transactions on Knowledge and Data Engineering (TKDE).
Xiyang Hu, Yan Huang, Beibei Li, Tian Lu (2021). Uncovering the Source of Evaluation Bias in Micro-Lending. Proceedings of International Conference on Information Systems (ICIS).
Xiyang Hu*, Yue Zhao*, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu (2021). SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection. Proceedings of Machine Learning and Systems (MLSys).
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