| 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 Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017 | 471 | 2017 |
| Ead: elastic-net attacks to deep neural networks via adversarial examples PY Chen, Y Sharma, H Zhang, J Yi, CJ Hsieh arXiv preprint arXiv:1709.04114, 2017 | 246 | 2017 |
| Evaluating the robustness of neural networks: An extreme value theory approach TW Weng, H Zhang, PY Chen, J Yi, D Su, Y Gao, CJ Hsieh, L Daniel arXiv preprint arXiv:1801.10578, 2018 | 129 | 2018 |
| Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D Su, H Zhang, H Chen, J Yi, PY Chen, Y Gao Proceedings of the European Conference on Computer Vision (ECCV), 631-648, 2018 | 113 | 2018 |
| Query-efficient hard-label black-box attack: An optimization-based approach M Cheng, T Le, PY Chen, J Yi, H Zhang, CJ Hsieh arXiv preprint arXiv:1807.04457, 2018 | 101 | 2018 |
| 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, 742-749, 2019 | 92 | 2019 |
| Semi-crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning J Yi, R Jin, A Jain, S Jain, T Yang Advances in Neural Information Processing Systems (NIPS), 1781-1789, 2012 | 87 | 2012 |
| Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples. M Cheng, J Yi, PY Chen, H Zhang, CJ Hsieh AAAI, 3601-3608, 2020 | 75 | 2020 |
| Practical machine learning S Gollapudi Packt Publishing Ltd, 2016 | 71 | 2016 |
| Diverse few-shot text classification with multiple metrics M Yu, X Guo, J Yi, S Chang, S Potdar, Y Cheng, G Tesauro, H Wang, ... arXiv preprint arXiv:1805.07513, 2018 | 67 | 2018 |
| Inferring Users’ Preferences from Crowdsourced Pairwise Comparisons: A Matrix Completion Approach J Yi, R Jin, S Jain, A Jain AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2013 | 67 | 2013 |
| Robust Ensemble Clustering by Matrix Completion J Yi, T Yang, R Jin, AK Jain, M Mahdavi IEEE International Conference on Data Mining (ICDM), 2012 | 67 | 2012 |
| Efficient Algorithms for Robust One-bit Compressive Sensing L Zhang, J Yi, R Jin International Conference on Machine Learning (ICML), 820-828, 2014 | 66 | 2014 |
| Attacking visual language grounding with adversarial examples: A case study on neural image captioning H Chen, H Zhang, PY Chen, J Yi, CJ Hsieh arXiv preprint arXiv:1712.02051, 2017 | 53 | 2017 |
| Tracking slowly moving clairvoyant: Optimal dynamic regret of online learning with true and noisy gradient T Yang, L Zhang, R Jin, J Yi International Conference on Machine Learning, 449-457, 2016 | 53 | 2016 |
| Efficient distance metric learning by adaptive sampling and mini-batch stochastic gradient descent (SGD) Q Qian, R Jin, J Yi, L Zhang, S Zhu Machine Learning 99 (3), 353-372, 2015 | 53 | 2015 |
| Crowdclustering with Sparse Pairwise Labels: A Matrix Completion Approach J Yi, R Jin, AK Jain, S Jain AAAI workshop on Human Computation (HCOMP), 2012 | 50 | 2012 |
| On the Convergence and Robustness of Adversarial Training. Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu ICML 1, 2, 2019 | 48 | 2019 |
| Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion J Yi, L Zhang, R Jin, Q Qian, A Jain International Conference on Machine Learning (ICML), 1400-1408, 2013 | 43 | 2013 |
| Improved Dynamic Regret for Non-degeneracy Functions L Zhang, T Yang, J Yi, R Jin, ZH Zhou arXiv preprint arXiv:1608.03933, 2016 | 42 | 2016 |
Rong JinAlibaba GroupVerified email at cse.msu.edu
