Kamu erişimi zorunlu olan makaleler - Huan ZhangDaha fazla bilgi edinin
Bir yerde sunuluyor: 35
Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models
PY Chen*, H Zhang*, Y Sharma, J Yi, CJ Hsieh
(*Equal Contribution) Proceedings of the 10th ACM workshop on artificial …, 2017
Zorunlu olanlar: US National Science Foundation
Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent
X Lian, C Zhang, H Zhang, CJ Hsieh, W Zhang, J Liu
Advances in Neural Information Processing Systems (NIPS) (oral presentation …, 2017
Zorunlu olanlar: US National Science Foundation, Swiss National Science Foundation
Efficient neural network robustness certification with general activation functions
H Zhang*, TW Weng*, PY Chen, CJ Hsieh, L Daniel
(*Equal Contribution) Advances in Neural Information Processing Systems …, 2018
Zorunlu olanlar: US National Science Foundation
Towards fast computation of certified robustness for relu networks
L Weng*, H Zhang*, H Chen, Z Song, CJ Hsieh, L Daniel, D Boning, ...
(*Equal Contribution) International Conference on Machine Learning (ICML …, 2018
Zorunlu olanlar: US National Science Foundation
Ead: elastic-net attacks to deep neural networks via adversarial examples
PY Chen, Y Sharma, H Zhang, J Yi, CJ Hsieh
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
Zorunlu olanlar: US National Science Foundation
Towards robust neural networks via random self-ensemble
X Liu, M Cheng, H Zhang, CJ Hsieh
Proceedings of the european conference on computer vision (ECCV), 369-385, 2018
Zorunlu olanlar: US National Science Foundation
Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks
CC Tu, P Ting, PY Chen, S Liu, H Zhang, J Yi, CJ Hsieh, SM Cheng
Proceedings of the AAAI conference on artificial intelligence 33 (01), 742-749, 2019
Zorunlu olanlar: US National Science Foundation
Beta-CROWN: Efficient bound propagation with per-neuron split constraints for complete and incomplete neural network verification
S Wang*, H Zhang*, K Xu*, X Lin, S Jana, CJ Hsieh, JZ Kolter
(*Equal Contribution) Advances in Neural Information Processing Systems …, 2021
Zorunlu olanlar: US National Science Foundation, US Department of Defense
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
H Zhang*, H Chen*, C Xiao, B Li, D Boning, CJ Hsieh
(*Equal Contribution) NeurIPS (spotlight) 33, 2020
Zorunlu olanlar: US National Science Foundation
Genattack: Practical black-box attacks with gradient-free optimization
M Alzantot, Y Sharma, S Chakraborty, H Zhang, CJ Hsieh, MB Srivastava
Proceedings of the genetic and evolutionary computation conference, 1111-1119, 2019
Zorunlu olanlar: US National Science Foundation, US Department of Defense, US National …
Automatic perturbation analysis for scalable certified robustness and beyond
K Xu*, Z Shi*, H Zhang*, Y Wang, KW Chang, M Huang, B Kailkhura, ...
(*Equal Contribution) Advances in Neural Information Processing Systems …, 2020
Zorunlu olanlar: US National Science Foundation, US Department of Energy, National Natural …
TrustLLM: Trustworthiness in large language models
L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ...
arXiv preprint arXiv:2401.05561, 2024
Zorunlu olanlar: US National Science Foundation
Adversarial robustness vs. model compression, or both?
S Ye, K Xu, S Liu, H Cheng, JH Lambrechts, H Zhang, A Zhou, K Ma, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision, 111-120, 2019
Zorunlu olanlar: US National Science Foundation
Gradient boosted decision trees for high dimensional sparse output
S Si, H Zhang, SS Keerthi, D Mahajan, IS Dhillon, CJ Hsieh
International Conference on Machine Learning (ICML), 3182-3190, 2017
Zorunlu olanlar: US National Science Foundation
Robust decision trees against adversarial examples
H Chen, H Zhang, D Boning, CJ Hsieh
International Conference on Machine Learning (ICML) 2019, 2019
Zorunlu olanlar: US National Science Foundation
A comprehensive linear speedup analysis for asynchronous stochastic parallel optimization from zeroth-order to first-order
X Lian, H Zhang, CJ Hsieh, Y Huang, J Liu
Advances in Neural Information Processing Systems (NIPS) 29, 3054-3062, 2016
Zorunlu olanlar: US National Science Foundation
General cutting planes for bound-propagation-based neural network verification
H Zhang, S Wang, K Xu, L Li, B Li, S Jana, CJ Hsieh, JZ Kolter
Advances in Neural Information Processing Systems (NeurIPS), 2022
Zorunlu olanlar: US National Science Foundation
Deep learning-based picture-wise just noticeable distortion prediction model for image compression
H Liu, Y Zhang, H Zhang, C Fan, S Kwong, CCJ Kuo, X Fan
IEEE Transactions on Image Processing 29, 641-656, 2019
Zorunlu olanlar: Chinese Academy of Sciences, National Natural Science Foundation of China
Robustness verification of tree-based models
H Chen*, H Zhang*, S Si, Y Li, D Boning, CJ Hsieh
(*Equal Contribution) Advances in Neural Information Processing Systems …, 2019
Zorunlu olanlar: US National Science Foundation
Training certifiably robust neural networks with efficient local lipschitz bounds
Y Huang, H Zhang, Y Shi, JZ Kolter, A Anandkumar
Advances in Neural Information Processing Systems (NeurIPS) 34, 22745-22757, 2021
Zorunlu olanlar: US Department of Defense
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