机构

• 自动化研究所 [11]
• 计算技术研究所 [5]
• 数学与系统科学研究院 [1]

采集方式

• OAI收割 [17]

内容类型

• 期刊论文 [17]

发表日期

• 2025 [1]
• 2024 [5]
• 2023 [3]
• 2022 [5]
• 2021 [2]
• 2020 [1]
• 更多

学科主题

筛选

浏览/检索结果: 共17条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 SPMGAE: Self-purified masked graph autoencoders release robust expression power 期刊论文  OAI收割 NEUROCOMPUTING, 2025, 卷号: 611, 页码: 14 作者:  Song, Shuhan;  Li, Ping;  Dun, Ming;  Zhang, Yuan;  Cao, Huawei   |  收藏  |  浏览/下载：3/0  |  提交时间：2024/12/06 Graph neural networks  Masked graph autoencoders  Robustness  Graph adversarial attacks   IDEA: Invariant defense for graph adversarial robustness 期刊论文  OAI收割 INFORMATION SCIENCES, 2024, 卷号: 680, 页码: 18 作者:  Tao, Shuchang;  Cao, Qi;  Shen, Huawei;  Wu, Yunfan;  Xu, Bingbing   |  收藏  |  浏览/下载：2/0  |  提交时间：2024/12/06 Invariant defense  Adversarial robustness  Causal feature  Graph neural networks   A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF COMPUTER VISION, 2024, 页码: 23 作者:  Liu, Chang;  Dong, Yinpeng;  Xiang, Wenzhao;  Yang, Xiao;  Su, Hang   |  收藏  |  浏览/下载：5/0  |  提交时间：2024/12/06 Robustness benchmark  Distribution shift  Pre-training  Adversarial training  Image classification   A prompt-based approach to adversarial example generation and robustness enhancement 期刊论文  OAI收割 FRONTIERS OF COMPUTER SCIENCE, 2024, 卷号: 18, 期号: 4, 页码: 12 作者:  Yang, Yuting;  Huang, Pei;  Cao, Juan;  Li, Jintao;  Lin, Yun   |  收藏  |  浏览/下载：22/0  |  提交时间：2024/05/20 robustness  adversarial example  prompt learning  pre-trained language model   Graph Adversarial Immunization for Certifiable Robustness 期刊论文  OAI收割 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2024, 卷号: 36, 期号: 4, 页码: 1597-1610 作者:  Tao, Shuchang;  Cao, Qi;  Shen, Huawei;  Wu, Yunfan;  Hou, Liang   |  收藏  |  浏览/下载：14/0  |  提交时间：2024/05/20 Adversarial attack  adversarial immunization  certifiable robustness  graph neural networks  node classification   Disentangled Text Representation Learning With Information-Theoretic Perspective for Adversarial Robustness 期刊论文  OAI收割 IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2024, 卷号: 32, 页码: 1237-1247 作者:  Zhao, Jiahao;  Mao, Wenji;  Zeng, Daniel Dajun   |  收藏  |  浏览/下载：3/0  |  提交时间：2024/07/03 Adversarial robustness  variation of information  disentangled text representation learning   Adversarial Heterogeneous Graph Neural Network for Robust Recommendation 期刊论文  OAI收割 IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2023, 页码: 12 作者:  Sang, Lei;  Xu, Min;  Qian, Shengsheng;  Wu, Xindong   |  收藏  |  浏览/下载：14/0  |  提交时间：2023/11/17 Perturbation methods  Motion pictures  Training  Graph neural networks  Robustness  Semantics  Predictive models  Adversarial training (AT)  graph neural network (GNN)  heterogeneous graph  recommendation   Robust Monitor for Industrial IoT Condition Prediction 期刊论文  OAI收割 IEEE INTERNET OF THINGS JOURNAL, 2023, 卷号: 10, 期号: 10, 页码: 8618-8629 作者:  Zhang, Xingwei;  Tian, Hu;  Zheng, Xiaolong;  Zeng, Daniel Dajun   |  收藏  |  浏览/下载：25/0  |  提交时间：2023/11/17 Perturbation methods  Monitoring  Industrial Internet of Things  Training  Predictive models  Robustness  Temperature sensors  Adversarial perturbation  adversarial training  Industrial Internet of Things (IIoT)  machine learning (ML)  temporal convolutional network (TCN)   Adversarial training with distribution normalization and margin balance 期刊论文  OAI收割 PATTERN RECOGNITION, 2023, 卷号: 136, 页码: 11 作者:  Cheng, Zhen;  Zhu, Fei;  Zhang, Xu-Yao;  Liu, Cheng-Lin   |  收藏  |  浏览/下载：48/0  |  提交时间：2023/01/09 Adversarial robustness  Adversarial training  Distribution normalization  Margin balance   ASCL: Adversarial supervised contrastive learning for defense against word substitution attacks 期刊论文  OAI收割 NEUROCOMPUTING, 2022, 卷号: 510, 页码: 59-68 作者:  Shi, Jiahui;  Li, Linjing;  Zeng, Daniel   |  收藏  |  浏览/下载：51/0  |  提交时间：2022/11/14 Adversarial example  Adversarial training  Model robustness  Contrastive learning  Natural language processing