Search Results for author: Binbin Liu

Found 7 papers, 3 papers with code

Boosting 3D Adversarial Attacks with Attacking On Frequency

no code implementations26 Jan 2022 Binbin Liu, Jinlai Zhang, Lyujie Chen, Jihong Zhu

Deep neural networks (DNNs) have been shown to be vulnerable to adversarial attacks.

3D Adversarial Attacks Beyond Point Cloud

1 code implementation25 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.

Adversarial Attack

The art of defense: letting networks fool the attacker

1 code implementation7 Apr 2021 Jinlai Zhang, Binbin Liu, Lyvjie Chen, Bo Ouyang, Jihong Zhu, Minchi Kuang, Houqing Wang, Yanmei Meng

Some deep neural networks are invariant to some input transformations, such as Pointnet is permutation invariant to the input point cloud.

PointCutMix: Regularization Strategy for Point Cloud Classification

2 code implementations5 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.

3D Point Cloud Classification Classification +2

NeuReduce: Reducing Mixed Boolean-Arithmetic Expressions by Recurrent Neural Network

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).

Online Newton Step Algorithm with Estimated Gradient

no code implementations25 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).

online learning

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