I know what you see: Power side-channel attack on convolutional neural network accelerators L Wei, B Luo, Y Li, Y Liu, Q Xu (ACSAC'18) Proceedings of the 34th Annual Computer Security Applications …, 2018 | 215 | 2018 |
DeepDyve: Dynamic Verification for Deep Neural Networks Y Li, M Li, B Luo, Y Tian, Q Xu (CCS'20) Proceedings of the 2020 ACM SIGSAC Conference on Computer and …, 2020 | 40 | 2020 |
AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference M Li, Y Li, Y Tian, L Jiang, Q Xu (DAC'21) 2021 58th ACM/IEEE Design Automation Conference, 2021 | 25 | 2021 |
D2NN: a fine-grained dual modular redundancy framework for deep neural networks Y Li, Y Liu, M Li, Y Tian, B Luo, Q Xu (ACSAC'19) Proceedings of the 35th Annual Computer Security Applications …, 2019 | 21 | 2019 |
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks Y Li, M Li, Q Lai, Y Liu, Q Xu (NeurIPS'21) Thirty-fifth Conference on Neural Information Processing Systems, 2021 | 19 | 2021 |
What you see is not what the network infers: detecting adversarial examples based on semantic contradiction Y Yang, R Gao, Y Li, Q Lai, Q Xu (NDSS'22) Network and Distributed Systems Security (NDSS) Symposium 2022, 2022 | 12 | 2022 |
On functional test generation for deep neural network ips B Luo, Y Li, L Wei, Q Xu (DATE'19) 2019 Design, Automation & Test in Europe Conference & Exhibition …, 2019 | 11 | 2019 |
IEEE Std P1838's flexible parallel port and its specification with Google's protocol buffers Y Li, M Shao, H Jiao, A Cron, S Bhatia, EJ Marinissen (ETS'18) 2018 IEEE 23rd European Test Symposium, 1-6, 2018 | 11 | 2018 |
HybridRepair: towards annotation-efficient repair for deep learning models Y Li, M Chen, Q Xu (ISSTA'22) Proceedings of the 31st ACM SIGSOFT International Symposium on …, 2022 | 7 | 2022 |
On Workload-Aware DRAM Failure Prediction in Large-Scale Data Centers X Wang, Y Li, Y Chen, S Wang, Y Du, C He, YZ Zhang, P Chen, X Li, ... (VTS'21) 2021 IEEE 39th VLSI Test Symposium, 1-6, 2021 | 7 | 2021 |
An empirical study on the efficacy of deep active learning for image classification Y Li, M Chen, Y Liu, D He, Q Xu arXiv preprint arXiv:2212.03088, 2022 | 5 | 2022 |
HiBug: On Human-Interpretable Model Debug M Chen, Y Li, Q Xu (NeurIPS'23)Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 4 | 2023 |
Information Bottleneck Approach to Spatial Attention Learning Q Lai, Y Li, A Zeng, M Liu, H Sun, Q Xu IJCAI 2021, 2021 | 4 | 2021 |
Mixdefense: A defense-in-depth framework for adversarial example detection based on statistical and semantic analysis Y Yang, R Gao, Y Li, Q Lai, Q Xu arXiv preprint arXiv:2104.10076, 2021 | 1 | 2021 |
On Configurable Defense against Adversarial Example Attacks B Luo, M Li, Y Li, Q Xu (GLSVLSI'20) Proceedings of the 2020 on Great Lakes Symposium on VLSI, 543-548, 2020 | 1 | 2020 |
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation J Zhou, L Lyu, D He, Y Li arXiv preprint arXiv:2402.15853, 2024 | | 2024 |
MEAOD: Model Extraction Attack against Object Detectors Z Li, C Shi, Y Pu, X Zhang, Y Li, J Li, S Ji arXiv preprint arXiv:2312.14677, 2023 | | 2023 |
Towards Robust Deep Neural Networks Against Design-Time and Run-Time Failures Y Li, Q Xu 2023 IEEE International Test Conference (ITC), 196-205, 2023 | | 2023 |
Self-supervised Video Representation Learning via Capturing Semantic Changes Indicated by Saccades Q Lai, A Zeng, Y Wang, L Cao, Y Li, Q Xu (TCSVT'23) IEEE Transactions on Circuits and Systems for Video Technology, 2023 | | 2023 |
EXPERT: EXPloiting DRAM ERror Types to Improve the Effective Forecasting Coverage in the Field X Peng, Z Huang, A Cantrell, BH Shu, KK Xie, Y Li, Y Li, L Jiang, Q Xu, ... 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems …, 2023 | | 2023 |