metric-learn: Metric Learning Algorithms in Python. - William de Vazelhes; CJ Carey; Yuan Tang; Nathalie Vauquier; Aurélien Bellet (J. Mach. Learn. Res., 2020)

Efficient Semi-Supervised Adversarial Training without Guessing Labels. - Huimin Wu; William de Vazelhes; Bin Gu 001 (ICDM, 2022)

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. - William de Vazelhes; Hualin Zhang; Huimin Wu; Xiaotong Yuan; Bin Gu 001 (NeurIPS, 2022)

Direct Training of SNN using Local Zeroth Order Method. - Bhaskar Mukhoty; Velibor Bojkovic; William de Vazelhes; Xiaohan Zhao; Giulia De Masi; Huan Xiong; Bin Gu 001 (NeurIPS, 2023)

Energy Efficient Training of SNN using Local Zeroth Order Method. - Bhaskar Mukhoty; Velibor Bojkovic; William de Vazelhes; Giulia De Masi; Huan Xiong; Bin Gu 001 (CoRR, 2023)

Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging. - Hilal AlQuabeh; William de Vazelhes; Bin Gu 001 (AAAI, 2024)

Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery. - William de Vazelhes; Bhaskar Mukhoty; Xiao-Tong Yuan; Bin Gu 001 (AAAI, 2024)

New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions. - Xinzhe Yuan; William de Vazelhes; Bin Gu 001; Huan Xiong (ICLR, 2024)

Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning. - Chengqian Gao; William de Vazelhes; Hualin Zhang; Bin Gu 001; Zhiqiang Xu (IJCAI, 2024)

Stagewise Training With Exponentially Growing Training Sets. - Bin Gu 001; Hilal AlQuabeh; William de Vazelhes; Zhouyuan Huo; Heng Huang (IEEE Trans. Neural Networks Learn. Syst., 2025)

Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees. - William de Vazelhes; Xiao-Tong Yuan; Bin Gu 001 (CoRR, 2025)