no code implementations • 25 Nov 2018 • Binbin Liu, Jundong Li, Yunquan Song, Xijun Liang, Ling Jian, Huan Liu
In particular, we extend the ONS algorithm with the trick of expected gradient and develop a novel second-order online learning algorithm, i. e., Online Newton Step with Expected Gradient (ONSEG).
no code implementations • Findings of the Association for Computational Linguistics 2020 • Weijie Feng, Binbin Liu, Dongpeng Xu, Qilong Zheng, Yun Xu
Mixed Boolean-Arithmetic (MBA) expressions involve both arithmetic calculation (e. g., plus, minus, multiply) and bitwise computation (e. g., and, or, negate, xor).
2 code implementations • 5 Jan 2021 • Jinlai Zhang, Lyujie Chen, Bo Ouyang, Binbin Liu, Jihong Zhu, Yujing Chen, Yanmei Meng, Danfeng Wu
As 3D point cloud analysis has received increasing attention, the insufficient scale of point cloud datasets and the weak generalization ability of networks become prominent.
Ranked #3 on 3D Point Cloud Classification on ModelNet40-C
1 code implementation • 7 Apr 2021 • Jinlai Zhang, Yinpeng Dong, Binbin Liu, Bo Ouyang, Jihong Zhu, Minchi Kuang, Houqing Wang, Yanmei Meng
To this end, in this paper, we propose a novel adversarial defense for 3D point cloud classifier that makes full use of the nature of the DNNs.
1 code implementation • 25 Apr 2021 • Jinlai Zhang, Lyujie Chen, Binbin Liu, Bo Ouyang, Qizhi Xie, Jihong Zhu, Weiming Li, Yanmei Meng
In order to take advantage of the most effective gradient-based attack, a differentiable sample module that back-propagate the gradient of point cloud to mesh is introduced.
1 code implementation • 26 Jan 2022 • Binbin Liu, Jinlai Zhang, Lyujie Chen, Jihong Zhu
Deep neural networks (DNNs) have been shown to be vulnerable to adversarial attacks.
no code implementations • EMNLP 2021 • Weijie Feng, Binbin Liu, Dongpeng Xu, Qilong Zheng, Yun Xu
Mathematical reasoning aims to infer satisfiable solutions based on the given mathematics questions.