no code implementations • 1 Jun 2019 • Binbin Jin, Enhong Chen, Hongke Zhao, Zhenya Huang, Qi Liu, HengShu Zhu, Shui Yu
Existing solutions mainly exploit the syntactic or semantic correlation between a question and its related answers (Q&A), where the multi-facet domain effects in CQA are still underexplored.
no code implementations • 25 Apr 2020 • Xiaozheng Xie, Jianwei Niu, Xuefeng Liu, Zhengsu Chen, Shaojie Tang, Shui Yu
Although deep learning models like CNNs have achieved great success in medical image analysis, the small size of medical datasets remains a major bottleneck in this area.
no code implementations • 18 Oct 2020 • Jianchao Lu, Xi Zheng, Tianyi Zhang, Michael Sheng, Chen Wang, Jiong Jin, Shui Yu, Wanlei Zhou
In this paper, we propose a novel driver fatigue detection method by embedding surface electromyography (sEMG) sensors on a steering wheel.
no code implementations • 1 Jan 2021 • Song Gao, Shui Yu, Shaowen Yao
In this paper, we utilize the steganalysis rich model (SRM) to generate noise feature maps, and combine them with RGB images to discover the difference between adversarial examples and clean examples.
no code implementations • 1 Jan 2021 • Bingbing Song, wei he, Renyang Liu, Shui Yu, Ruxin Wang, Mingming Gong, Tongliang Liu, Wei Zhou
Several state-of-the-arts start from improving the inter-class separability of training samples by modifying loss functions, where we argue that the adversarial samples are ignored and thus limited robustness to adversarial attacks is resulted.
no code implementations • 11 Jan 2021 • Yao Fu, Yipeng Zhou, Di wu, Shui Yu, Yonggang Wen, Chao Li
Then, we theoretically derive: 1) the conditions for the DP based FedAvg to converge as the number of global iterations (GI) approaches infinity; 2) the method to set the number of local iterations (LI) to minimize the negative influence of DP noises.
no code implementations • 15 Apr 2021 • Shuiqiao Yang, Sunny Verma, Borui Cai, Jiaojiao Jiang, Kun Yu, Fang Chen, Shui Yu
Recent works for attributed network clustering utilize graph convolution to obtain node embeddings and simultaneously perform clustering assignments on the embedding space.
1 code implementation • 5 Jul 2021 • Yipeng Zhou, Xuezheng Liu, Yao Fu, Di wu, Chao Li, Shui Yu
In this work, we study a crucial question which has been vastly overlooked by existing works: what are the optimal numbers of queries and replies in FL with DP so that the final model accuracy is maximized.
no code implementations • 29 Nov 2021 • Tian Liu, Zhiwei Ling, Jun Xia, Xin Fu, Shui Yu, Mingsong Chen
Inspired by Knowledge Distillation (KD) that can increase the model accuracy, our approach adds the soft targets used by KD to the FL model training, which occupies negligible network resources.
no code implementations • 28 Feb 2022 • Bo Li, Ting Wang, Peng Yang, Mingsong Chen, Shui Yu, Mounir Hamdi
To support the needs of ever-growing cloud-based services, the number of servers and network devices in data centers is increasing exponentially, which in turn results in high complexities and difficulties in network optimization.
no code implementations • 25 Dec 2022 • Yuntao Wang, Zhou Su, Yanghe Pan, Tom H Luan, Ruidong Li, Shui Yu
In this paper, we strike the balance of data privacy and efficiency by utilizing the pervasive social connections between users.
1 code implementation • 25 May 2023 • Jiahao Tan, Yipeng Zhou, Gang Liu, Jessie Hui Wang, Shui Yu
More specifically, we decouple a NN model into a personalized feature extractor, obtained by aggregating models from similar clients, and a classifier, which is obtained by local training and used to estimate client similarity.
no code implementations • 30 May 2023 • Jiwei Guan, Lei Pan, Chen Wang, Shui Yu, Longxiang Gao, Xi Zheng
As deep learning has been applied to increasingly sensitive tasks, uncertainty measurement is crucial in helping improve model robustness, especially in mission-critical scenarios.
no code implementations • 29 Jun 2023 • Youyang Qu, Lichuan Ma, Wenjie Ye, Xuemeng Zhai, Shui Yu, Yunfeng Li, David Smith
Linkage attack is a type of dominant attack in the privacy domain, which can leverage various data sources for private data mining.
1 code implementation • 11 Dec 2023 • Yuyang Zhou, Guang Cheng, Zongyao Chen, Shui Yu
Experimental results on two Android malware datasets demonstrate that MalPurifier outperforms the state-of-the-art defenses, and it significantly strengthens the vulnerable malware detector against 37 evasion attacks, achieving accuracies over 90. 91%.
no code implementations • 18 Feb 2024 • Yakun Chen, Kaize Shi, Zhangkai Wu, Juan Chen, Xianzhi Wang, Julian McAuley, Guandong Xu, Shui Yu
Spatiotemporal data analysis is pivotal across various domains, such as transportation, meteorology, and healthcare.