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ORCIDWilliam de Vazelhes
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2020 – today
- 2024
[c6]Hilal AlQuabeh, William de Vazelhes, Bin Gu:
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging. AAAI 2024: 10821-10828- [c5]William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu:
Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery. AAAI 2024: 11731-11739 - [c4]Xinzhe Yuan, William de Vazelhes, Bin Gu, Huan Xiong:
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions. ICLR 2024 - [i6]William de Vazelhes, Bhaskar Mukhoty, Xiao-Tong Yuan, Bin Gu:
Iterative Regularization with k-Support Norm: An Important Complement to Sparse Recovery. CoRR abs/2401.05394 (2024) - [i5]Hilal AlQuabeh, William de Vazelhes, Bin Gu:
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging. CoRR abs/2402.01146 (2024) - [i4]Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu:
Hard-Thresholding Meets Evolution Strategies in Reinforcement Learning. CoRR abs/2405.01615 (2024) - 2023
- [c3]Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Xiaohan Zhao, Giulia De Masi, Huan Xiong, Bin Gu:
Direct Training of SNN using Local Zeroth Order Method. NeurIPS 2023 - [i3]Bhaskar Mukhoty, Velibor Bojkovic, William de Vazelhes, Giulia De Masi, Huan Xiong, Bin Gu:
Energy Efficient Training of SNN using Local Zeroth Order Method. CoRR abs/2302.00910 (2023) - 2022
- [c2]Huimin Wu, William de Vazelhes, Bin Gu:
Efficient Semi-Supervised Adversarial Training without Guessing Labels. ICDM 2022: 538-547 - [c1]William de Vazelhes, Hualin Zhang, Huimin Wu, Xiaotong Yuan, Bin Gu:
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. NeurIPS 2022 - [i2]William de Vazelhes, Hualin Zhang, Huimin Wu, Xiao-Tong Yuan, Bin Gu:
Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity. CoRR abs/2210.05279 (2022) - 2020
- [j1]William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet:
metric-learn: Metric Learning Algorithms in Python. J. Mach. Learn. Res. 21: 138:1-138:6 (2020)
2010 – 2019
- 2019
- [i1]William de Vazelhes, CJ Carey, Yuan Tang
, Nathalie Vauquier, Aurélien Bellet:
metric-learn: Metric Learning Algorithms in Python. CoRR abs/1908.04710 (2019)
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