Search Results for author: Zhuoer Xu

Found 9 papers, 8 papers with code

Backpropagation Path Search On Adversarial Transferability

no code implementations ICCV 2023 Zhuoer Xu, Zhangxuan Gu, Jianping Zhang, Shiwen Cui, Changhua Meng, Weiqiang Wang

Transfer-based attackers craft adversarial examples against surrogate models and transfer them to victim models deployed in the black-box situation.

Bayesian Optimization

On the Robustness of Latent Diffusion Models

1 code implementation14 Jun 2023 Jianping Zhang, Zhuoer Xu, Shiwen Cui, Changhua Meng, Weibin Wu, Michael R. Lyu

Therefore, in this paper, we aim to analyze the robustness of latent diffusion models more thoroughly.

Denoising Image Generation

DiffUTE: Universal Text Editing Diffusion Model

1 code implementation18 May 2023 Haoxing Chen, Zhuoer Xu, Zhangxuan Gu, Jun Lan, Xing Zheng, Yaohui Li, Changhua Meng, Huijia Zhu, Weiqiang Wang

Specifically, we build our model on a diffusion model and carefully modify the network structure to enable the model for drawing multilingual characters with the help of glyph and position information.

Glyph Image Generation Image Generation +2

AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network

1 code implementation8 Jan 2023 Guanghui Zhu, Zhennan Zhu, Wenjie Wang, Zhuoer Xu, Chunfeng Yuan, Yihua Huang

Moreover, to improve the performance of the downstream graph learning task, attribute completion and the training of the heterogeneous GNN should be jointly optimized rather than viewed as two separate processes.

Graph Learning Node Clustering

DiffusionInst: Diffusion Model for Instance Segmentation

2 code implementations6 Dec 2022 Zhangxuan Gu, Haoxing Chen, Zhuoer Xu, Jun Lan, Changhua Meng, Weiqiang Wang

Extensive experimental results on COCO and LVIS show that DiffusionInst achieves competitive performance compared to existing instance segmentation models with various backbones, such as ResNet and Swin Transformers.

Instance Segmentation

A2: Efficient Automated Attacker for Boosting Adversarial Training

1 code implementation7 Oct 2022 Zhuoer Xu, Guanghui Zhu, Changhua Meng, Shiwen Cui, ZhenZhe Ying, Weiqiang Wang, Ming Gu, Yihua Huang

In this paper, we propose an efficient automated attacker called A2 to boost AT by generating the optimal perturbations on-the-fly during training.

Adversarial Defense

MT-GBM: A Multi-Task Gradient Boosting Machine with Shared Decision Trees

1 code implementation17 Jan 2022 ZhenZhe Ying, Zhuoer Xu, Zhifeng Li, Weiqiang Wang, Changhua Meng

Despite the success of deep learning in computer vision and natural language processing, Gradient Boosted Decision Tree (GBDT) is yet one of the most powerful tools for applications with tabular data such as e-commerce and FinTech.

Multi-Task Learning

DIFER: Differentiable Automated Feature Engineering

1 code implementation17 Oct 2020 Guanghui Zhu, Zhuoer Xu, Xu Guo, Chunfeng Yuan, Yihua Huang

Extensive experiments on classification and regression datasets demonstrate that DIFER can significantly improve the performance of various machine learning algorithms and outperform current state-of-the-art AutoFE methods in terms of both efficiency and performance.

Automated Feature Engineering BIG-bench Machine Learning +1

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