no code implementations • 4 May 2022 • Youhuan Yang, Lei Sun, Leyu Dai, Song Guo, Xiuqing Mao, Xiaoqin Wang, Bayi Xu
This is especially dangerous for some systems with high-security requirements, so this paper proposes a new defense method by using the model super-fitting state to improve the model's adversarial robustness (i. e., the accuracy under adversarial attacks).
no code implementations • 4 May 2022 • Youhuan Yang, Lei Sun, Leyu Dai, Song Guo, Xiuqing Mao, Xiaoqin Wang, Bayi Xu
Various defense models have been proposed to resist adversarial attack algorithms, but existing adversarial robustness evaluation methods always overestimate the adversarial robustness of these models (i. e., not approaching the lower bound of robustness).
no code implementations • 14 Apr 2022 • Feijie Wu, Shiqi He, Song Guo, Zhihao Qu, Haozhao Wang, Weihua Zhuang, Jie Zhang
Traditional one-bit compressed stochastic gradient descent can not be directly employed in multi-hop all-reduce, a widely adopted distributed training paradigm in network-intensive high-performance computing systems such as public clouds.
no code implementations • 7 Mar 2022 • Ziming Liu, Song Guo, Jingcai Guo, Yuanyuan Xu, Fushuo Huo
We argue that disregarding the connection between major and minor classes, i. e., correspond to the global and local information, respectively, is the cause of the problem.
no code implementations • 27 Feb 2022 • Tao Guo, Song Guo, Jiewei Zhang, Wenchao Xu, Junxiao Wang
Existing studies of machine unlearning mainly focus on sample-wise unlearning, such that a learnt model will not expose user's privacy at the sample level.
no code implementations • 5 Feb 2022 • Leijie Wu, Song Guo, Yaohong Ding, Yufeng Zhan, Jie Zhang
Facing the challenge of statistical diversity in client local data distribution, personalized federated learning (PFL) has become a growing research hotspot.
no code implementations • 17 Dec 2021 • Feijie Wu, Song Guo, Haozhao Wang, Zhihao Qu, Haobo Zhang, Jie Zhang, Ziming Liu
In the setting of federated optimization, where a global model is aggregated periodically, step asynchronism occurs when participants conduct model training with fully utilizing their computational resources.
no code implementations • NeurIPS 2021 • Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wencao Xu, Feijie Wu
To deal with such model constraints, we exploit the potentials of heterogeneous model settings and propose a novel training framework to employ personalized models for different clients.
no code implementations • 22 Oct 2021 • Junxiao Wang, Song Guo, Xin Xie, Heng Qi
Evaluated on CIFAR10 dataset, our method accelerates the speed of unlearning by 8. 9x for the ResNet model, and 7. 9x for the VGG model under no degradation in accuracy, compared to retraining from scratch.
no code implementations • 26 Sep 2021 • Jun Du, Chunxiao Jiang, Abderrahim Benslimane, Song Guo, Yong Ren
Based on this dynamic access model, a Stackelberg differential game based cloud computing resource sharing mechanism is proposed to facilitate the resource trading between the cloud computing service provider (CCP) and different edge computing service providers (ECPs).
no code implementations • 24 Jun 2021 • Xueyang Tang, Song Guo, Jingcai Guo
The prevalent personalized federated learning (PFL) usually pursues a trade-off between personalization and generalization by maintaining a shared global model to guide the training process of local models.
no code implementations • 15 Apr 2021 • Yuben Qu, Haipeng Dai, Yan Zhuang, Jiafa Chen, Chao Dong, Fan Wu, Song Guo
Unmanned aerial vehicles (UAVs), or say drones, are envisioned to support extensive applications in next-generation wireless networks in both civil and military fields.
1 code implementation • CVPR 2021 • Song Guo, Jingya Wang, Xinchao Wang, DaCheng Tao
On the other hand, such reliable embeddings can boost identity-awareness through memory aggregation, hence strengthen attention modules and suppress drifts.
1 code implementation • 25 Sep 2020 • Song Guo
2) The segmentation speed of DPN is over 20-160 times faster than other methods on the DRIVE dataset.
no code implementations • 10 Aug 2020 • Jiawen Kang, Zehui Xiong, Chunxiao Jiang, Yi Liu, Song Guo, Yang Zhang, Dusit Niyato, Cyril Leung, Chunyan Miao
This framework can achieve scalable and flexible decentralized FEL by individually manage local model updates or model sharing records for performance isolation.
Cryptography and Security
no code implementations • 30 Apr 2020 • Jingcai Guo, Song Guo
One common practice in zero-shot learning is to train a projection between the visual and semantic feature spaces with labeled seen classes examples.
no code implementations • 3 Feb 2020 • Huawei Huang, Kangying Lin, Song Guo, Pan Zhou, Zibin Zheng
In the dynamic environment, the mobile devices selected by the existing reactive candidate-selection algorithms very possibly fail to complete the training and reporting phases of FL, because the FL parameter server only knows the currently-observed resources of all candidates.
no code implementations • 22 Jan 2020 • Haozhao Wang, Zhihao Qu, Song Guo, Xin Gao, Ruixuan Li, Baoliu Ye
A major bottleneck on the performance of distributed Stochastic Gradient Descent (SGD) algorithm for large-scale Federated Learning is the communication overhead on pushing local gradients and pulling global model.
no code implementations • 17 Dec 2019 • Sicong Zhou, Huawei Huang, Wuhui Chen, Zibin Zheng, Song Guo
Therefore, to provide the byzantine-resilience for distributed learning in 5G era, this article proposes a secure computing framework based on the sharding-technique of blockchain, namely PIRATE.
Distributed, Parallel, and Cluster Computing Cryptography and Security
no code implementations • 21 Apr 2019 • Hongji Huang, Song Guo, Guan Gui, Zhen Yang, Jianhua Zhang, Hikmet Sari, Fumiyuki Adachi
The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications.
no code implementations • 12 Apr 2019 • Jingcai Guo, Shiheng Ma, Song Guo
Specifically, we propose the local aware (LA) and global aware (GA) attention to deal with LR features in unequal manners, which can highlight the high-frequency components and discriminate each feature from LR images in the local and the global views, respectively.
no code implementations • 12 Apr 2019 • Shiheng Ma, Jingcai Guo, Song Guo, Minyi Guo
Our approach employs the inception backbone network to capture rich features of traffic distribution on the whole area.
no code implementations • 12 Apr 2019 • Jingcai Guo, Song Guo
It considers the Alignment of Manifold Structures by Semantic Feature Expansion.
no code implementations • 30 Mar 2019 • Jingcai Guo, Song Guo
To the best of our knowledge, our work is the first to consider the adaptive adjustment of semantic FS in ZSR.
no code implementations • 30 Mar 2019 • Jingcai Guo, Song Guo
In order to deal with this issue, we propose an Exclusivity Enhanced (EE) unsupervised feature learning approach to improve the conventional AE.
no code implementations • 21 Feb 2019 • Chengjie Li, Ruixuan Li, Haozhao Wang, Yuhua Li, Pan Zhou, Song Guo, Keqin Li
Distributed asynchronous offline training has received widespread attention in recent years because of its high performance on large-scale data and complex models.
1 code implementation • 11 Mar 2018 • Song Guo, Kai Wang, Hong Kang, Yujun Zhang, Yingqi Gao, Tao Li
Results: The proposed BTS-DSN has been verified on DRIVE, STARE and CHASE_DB1 datasets, and showed competitive performance over other state-of-the-art methods.