Research Group

Jiachen Jiang

MS, UMich; BS, Beihang

• J. Jiang, J. Zhou, P. Wang, Q. Qu, D. Mixon, C. You, Z. Zhu, Generalized Neural Collapse for a Large Number of Classes, 2023.

Hamoud Alhazmi

MS & BS, University of Canberra

Jinxin Zhou

MS, UMich; BS, HUST

• J. Zhou, C. You, X. Li, K. Liu, S. Liu, Q. Qu, and Z. Zhu, ‘‘Are All Losses Created Equal: A Neural Collapse Perspective," Neural Information Processing Systems (NeurIPS), December 2022.

• J. Zhou*, X. Li*, T. Ding, C. You, Q. Qu, and Z. Zhu, “On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features,” International Conference in Machine Learning (ICML), 2022. (acceptance rate = 20%)

• Z. Zhu*, T. Ding*, J. Zhou, X. Li, C. You, J. Sulam, and Q. Qu, ‘‘A Geometric Analysis of Neural Collapse with Unconstrained Features," Neural Information Processing Systems (NeurIPS), December 2021. (spotlight, top 3% ; acceptance rate = 26%)

Zhen Qin

MS, SEU; BS, LDU

• Z. Qin, A. Lidiak, Z. Gong, G. Tang, M. B. Wakin, and Z. Zhu, ‘‘Error Analysis of Tensor-Train Cross Approximation," Neural Information Processing Systems (NeurIPS), December 2022.

• A. Lidiak, C. Jameson, Z. Qin, G. Tang, M. B. Wakin, Z. Zhu, and Z. Gong, ‘‘Quantum state tomography with tensor train cross approximation,", preprint, 2022.

• H. Yu, Z. Qin, and Z. Zhu, “Learning Approach for Fast Approximate Matrix Factorizations,” International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.

Xi Chen

co-advising with Andrew Perrault

Shreya Byreddy

BS, OSU

Xinle Wu

Aalborg University, Denmark

Haiyan Yu

• H. Yu, Z. Qin, and Z. Zhu, “Learning Approach for Fast Approximate Matrix Factorizations,” International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.