| 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 | 176 | 2019 |
| On the convergence of a class of adam-type algorithms for non-convex optimization X Chen, S Liu, R Sun, M Hong arXiv preprint arXiv:1808.02941, 2018 | 163 | 2018 |
| Sensor selection for estimation with correlated measurement noise S Liu, SP Chepuri, M Fardad, E Maşazade, G Leus, PK Varshney IEEE Transactions on Signal Processing 64 (13), 3509-3522, 2016 | 121 | 2016 |
| 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 arXiv preprint arXiv:1906.04214, 2019 | 116 | 2019 |
| Learning sparse graphs under smoothness prior SP Chepuri, S Liu, G Leus, AO Hero 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 102 | 2017 |
| Structured adversarial attack: Towards general implementation and better interpretability K Xu, S Liu, P Zhao, PY Chen, H Zhang, Q Fan, D Erdogmus, Y Wang, ... arXiv preprint arXiv:1808.01664, 2018 | 92 | 2018 |
| Optimal periodic sensor scheduling in networks of dynamical systems S Liu, M Fardad, E Masazade, PK Varshney IEEE Transactions on Signal Processing 62 (12), 3055-3068, 2014 | 84 | 2014 |
| Zeroth-order stochastic variance reduction for nonconvex optimization S Liu, B Kailkhura, PY Chen, P Ting, S Chang, L Amini arXiv preprint arXiv:1805.10367, 2018 | 80 | 2018 |
| Cnn-cert: An efficient framework for certifying robustness of convolutional neural networks A Boopathy, TW Weng, PY Chen, S Liu, L Daniel Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3240-3247, 2019 | 78 | 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 European Conference on Computer Vision, 665-681, 2020 | 69* | 2020 |
| Adversarial robustness: From self-supervised pre-training to fine-tuning T Chen, S Liu, S Chang, Y Cheng, L Amini, Z Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 66 | 2020 |
| 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 | 63* | 2019 |
| Zeroth-order online alternating direction method of multipliers: Convergence analysis and applications S Liu, J Chen, PY Chen, A Hero International Conference on Artificial Intelligence and Statistics, 288-297, 2018 | 63 | 2018 |
| The lottery ticket hypothesis for pre-trained bert networks T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin arXiv preprint arXiv:2007.12223, 2020 | 56 | 2020 |
| Sign-opt: A query-efficient hard-label adversarial attack M Cheng, S Singh, P Chen, PY Chen, S Liu, CJ Hsieh arXiv preprint arXiv:1909.10773, 2019 | 54 | 2019 |
| Sparsity-aware sensor collaboration for linear coherent estimation S Liu, S Kar, M Fardad, PK Varshney IEEE Transactions on Signal Processing 63 (10), 2582-2596, 2015 | 51 | 2015 |
| Automated machine learning via ADMM S Liu, P Ram, D Bouneffouf, G Bramble, AR Conn, H Samulowitz, ... CoRR, vol. abs/1905.00424, 2019 | 42* | 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 Proceedings of the IEEE/CVF International Conference on Computer Vision, 121-130, 2019 | 37 | 2019 |
| A unified framework of dnn weight pruning and weight clustering/quantization using admm S Ye, T Zhang, K Zhang, J Li, J Xie, Y Liang, S Liu, X Lin, Y Wang arXiv preprint arXiv:1811.01907, 2018 | 36 | 2018 |
| 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 | 34 | 2019 |
Pin-Yu ChenResearch Staff Member, IBM Research AI; MIT-IBM Watson AI Lab; RPI-IBM AIRCVerified email at ibm.com
