William de Vazelhes

According to our database, William de Vazelhes authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning.

Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions.

Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery.

William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging.

Hilal AlQuabeh, William de Vazelhes, Bin Gu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

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

CoRR, 2023

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity.

William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Semi-Supervised Adversarial Training without Guessing Labels.

Huimin Wu, William de Vazelhes, Bin Gu

Proceedings of the IEEE International Conference on Data Mining, 2022

2020

metric-learn: Metric Learning Algorithms in Python.

William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet

J. Mach. Learn. Res., 2020