Benchmarking features from different radiomics toolkits / toolboxes using Image Biomarkers Standardization Initiative. - Mingxi Lei; Bino A. Varghese; Darryl Hwang; Steven Y. Cen; Xiaomeng Lei; Afshin Azadikhah; Desai Bhushan; Assad A. Oberai; Vinay A. Duddalwar (CoRR, 2020)

Wavelet-based CNN for Predicting PAP Adherence Using Overnight Polysomnography Recordings: a Pilot Study. - Mingxi Lei; Tom Maxim; Edwin Valladares; Eric Kezirian; B. Keith Jenkins (EMBC, 2021)

Benchmarking Various Radiomic Toolkit Features While Applying the Image Biomarker Standardization Initiative toward Clinical Translation of Radiomic Analysis. - Mingxi Lei; Bino A. Varghese; Darryl Hwang; Steven Y. Cen; Xiaomeng Lei; Desai Bhushan; Afshin Azadikhah; Assad A. Oberai; Vinay A. Duddalwar (J. Digit. Imaging, 2021)

Revisiting Differentially Private ReLU Regression. - Meng Ding; Mingxi Lei; Liyang Zhu; Shaowei Wang 003; Di Wang 015; Jinhui Xu 001 (NeurIPS, 2024)

Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization. - Ruijia Zhang; Mingxi Lei; Meng Ding; Zihang Xiang; Jinhui Xu 001; Di Wang 015 (AAAI, 2025)

TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram. - Mingxi Lei; Chunwei Ma; Meng Ding; Yufan Zhou 001; Ziyun Huang; Jinhui Xu 001 (ICLR, 2025)

Nearly Optimal Differentially Private ReLU Regression. - Meng Ding; Mingxi Lei; Shaowei Wang 003; Tianhang Zheng; Di Wang 015; Jinhui Xu 001 (UAI, 2025)

Unifying domain gap in Federated Learning: A geometric approach. - Mingxi Lei; Meng Ding; Chunwei Ma; Ziyun Huang; Mingchen Gao; Jinhui Xu 001 (Neurocomputing, 2025)

Towards User-level Private Reinforcement Learning with Human Feedback. - Jiaming Zhang; Mingxi Lei; Meng Ding; Mengdi Li; Zihang Xiang; Difei Xu; Jinhui Xu 001; Di Wang 015 (CoRR, 2025)