Computational and informational limits in high-dimensional statistical problems. Stanford University, 2024.

Shuangping Li*, Tselil Schramm*, Kangjie Zhou* (2024). Discrepancy Algorithms for the Binary Perceptron. arxiv preprint.

Andrea Montanari*, Kangjie Zhou* (2024). Which exceptional low-dimensional projections of a Gaussian point cloud can be found in polynomial time? arxiv preprint.

Fangyi Chen*, Yunxiao Chen*, Zhiliang Ying*, Kangjie Zhou* (2024). Dynamic Factor Analysis of High-dimensional Recurrent Events. arxiv preprint.

Yuchen Wu*, Kangjie Zhou* (2024). Sharp Analysis of Power Iteration for Tensor PCA. Journal of Machine Learning Research, 2024.

Andrea Montanari*, Yiqiao Zhong*, Kangjie Zhou* (2024). Tractability from overparametrization: The example of the negative perceptron. Probability Theory and Related Fields, 2024.

Raphaël Berthier*, Andrea Montanari*, Kangjie Zhou* (2023). Learning time-scales in two-layers neural networks. Foundations of Computational Mathematics, to appear.

Yuchen Wu*, Kangjie Zhou* (2023). Lower bounds for the convergence of tensor power iteration on random overcomplete models. Conference on Learning Theory, 2023.

Andrea Montanari*, Kangjie Zhou* (2022). Overparametrized linear dimensionality reductions: From projection pursuit to two-layer neural networks. arxiv preprint.

Kangjie Zhou, Andrea Montanari (2022). High-dimensional projection pursuit: Outer bounds and applications to interpolation in neural networks. Conference on Learning Theory, 2022.

Kangjie Zhou, Jinzhu Jia (2021). Propensity score adapted covariate selection for causal inference. arxiv preprint.

* Alphabetical