Math @ Duke
Xiuyuan Cheng, Assistant Professor
As an applied analyst, I develop theoretical and computational techniques to solve problems in high-dimensional statistics, signal processing and machine learning.
- Contact Info:
- Recent Publications
- Cheng, X; Cloninger, A; Coifman, RR, Two-sample statistics based on anisotropic kernels,
Information and Inference
(December, 2019), Oxford University Press (OUP) [doi] [abs]
- Cheng, X; Rachh, M; Steinerberger, S, On the diffusion geometry of graph Laplacians and applications,
Applied and Computational Harmonic Analysis, vol. 46 no. 3
pp. 674-688, Elsevier BV [doi]
- Cheng, X; Qiu, Q; Calderbank, R; Sapiro, G, RoTDCF: Decomposition of convolutional filters for rotation-equivariant deep networks,
7th International Conference on Learning Representations, Iclr 2019
(January, 2019) [abs]
- Cheng, X; Mishne, G; Steinerberger, S, The geometry of nodal sets and outlier detection,
Journal of Number Theory, vol. 185
pp. 48-64, Elsevier BV [doi]
- Yan, B; Sarkar, P; Cheng, X, Provable estimation of the number of blocks in block models,
International Conference on Artificial Intelligence and Statistics, Aistats 2018
pp. 1185-1194 [abs]
- Recent Grant Support
- HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2022/09.
- Sloan Foundation Fellowship for Xiuyuan Cheng in Mathematics, Alfred P. Sloan Foundation, 2019/09-2021/09.
- CDS&E: Structure-aware Representation Learning using Deep Networks, National Science Foundation, DMS-NSF-1820827-01, 2018/07-2021/06.
- Collaborative Research: Geometric Analysis and Computation of Generative Models, National Science Foundation, DMS-1818945, 2018/07-2021/06.
Duke University, Box 90320
Durham, NC 27708-0320