Kaidi Xu
Kaidi Xu
Northeastern University
Verified email at northeastern.edu - Homepage
Cited by
Cited by
Structured adversarial attack: Towards general implementation and better interpretability
K Xu, S Liu, P Zhao, PY Chen, H Zhang, D Erdogmus, Y Wang, X Lin
ICLR 2019, 2018
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
K Xu, H Chen, S Liu, PY Chen, TW Weng, M Hong, X Lin
IJCAI 2019, 2019
Progressive dnn compression: A key to achieve ultra-high weight pruning and quantization rates using admm
S Ye, X Feng, T Zhang, X Ma, S Lin, Z Li, K Xu, W Wen, S Liu, J Tang, ...
arXiv preprint arXiv:1903.09769, 2019
Adversarial Robustness vs. Model Compression, or Both?
S Ye, K Xu, S Liu, H Cheng, JH Lambrechts, H Zhang, A Zhou, K Ma, ...
ICCV 2019, 2019
Adversarial t-shirt! evading person detectors in a physical world
K Xu, G Zhang, S Liu, Q Fan, M Sun, H Chen, PY Chen, Y Wang, X Lin
(Spotlight) ECCV 2020, 665-681, 2020
Asymmetric discrete graph hashing
X Shi, F Xing, K Xu, M Sapkota, L Yang
AAAI 2017, 2017
REQ-YOLO: A resource-aware, efficient quantization framework for object detection on FPGAs
C Ding, S Wang, N Liu, K Xu, Y Wang, Y Liang
Proceedings of the 2019 ACM/SIGDA International Symposium on Field …, 2019
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
P Zhao, S Liu, PY Chen, N Hoang, K Xu, B Kailkhura, X Lin
ICCV 2019, 2019
Interpreting adversarial examples by activation promotion and suppression
K Xu, S Liu, G Zhang, M Sun, P Zhao, Q Fan, C Gan, X Lin
arXiv preprint arXiv:1904.02057, 2019
Supervised graph hashing for histopathology image retrieval and classification
X Shi, F Xing, K Xu, Y Xie, H Su, L Yang
Medical image analysis 42, 117-128, 2017
ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization
X Chen, S Liu, K Xu, X Li, X Lin, M Hong, D Cox
NeurIPS 2019, 2019
Min-max optimization without gradients: Convergence and applications to black-box evasion and poisoning attacks
S Liu, S Lu, X Chen, Y Feng, K Xu, A Al-Dujaili, M Hong, UM O’Reilly
ICML 2020, 2020
Admm attack: an enhanced adversarial attack for deep neural networks with undetectable distortions
P Zhao, K Xu, S Liu, Y Wang, X Lin
Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019
Defending against Backdoor Attack on Deep Neural Networks
H Cheng, K Xu, S Liu, PY Chen, P Zhao, X Lin
KDD 2019 AdvML workshop, 2020
Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond
K Xu, Z Shi, H Zhang, Y Wang, KW Chang, M Huang, B Kailkhura, X Lin, ...
NeurIPS 2020, 2020
Brain-inspired reverse adversarial examples
S Ye, SH Tan, K Xu, Y Wang, C Bao, K Ma
arXiv preprint arXiv:1905.12171, 2019
Reinforced adversarial attacks on deep neural networks using admm
P Zhao, K Xu, T Zhang, M Fardad, Y Wang, X Lin
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers
K Xu, H Zhang, S Wang, Y Wang, S Jana, X Lin, CJ Hsieh
ICLR 2021, 2020
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
S Ye, K Wu, M Zhou, Y Yang, K Xu, J Song, C Bao, K Ma
CVPR 2020, 2019
On Fast Adversarial Robustness Adaption in Model-Agnostic Meta-Learning
R Wang, K Xu, S Liu, PY Chen, TW Weng, C Gan, M Wang
ICLR 2021, 0
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