Cho-Jui Hsieh
Title
Cited by
Cited by
Year
LIBLINEAR: A library for large linear classification
RE Fan, KW Chang, CJ Hsieh, XR Wang, CJ Lin
the Journal of machine Learning research 9, 1871-1874, 2008
87022008
A dual coordinate descent method for large-scale linear SVM
CJ Hsieh, KW Chang, CJ Lin, SS Keerthi, S Sundararajan
Proceedings of the 25th international conference on Machine learning, 408-415, 2008
10422008
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
7592017
Training and testing low-degree polynomial data mappings via linear SVM.
YW Chang, CJ Hsieh, KW Chang, M Ringgaard, CJ Lin
Journal of Machine Learning Research 11 (4), 2010
4962010
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
arXiv preprint arXiv:1705.09056, 2017
4402017
Sparse inverse covariance matrix estimation using quadratic approximation
CJ Hsieh, MA Sustik, IS Dhillon, P Ravikumar
arXiv preprint arXiv:1306.3212, 2013
3832013
Ead: elastic-net attacks to deep neural networks via adversarial examples
PY Chen, Y Sharma, H Zhang, J Yi, CJ Hsieh
Thirty-second AAAI conference on artificial intelligence, 2018
3532018
Towards fast computation of certified robustness for relu networks
L Weng, H Zhang, H Chen, Z Song, CJ Hsieh, L Daniel, D Boning, ...
International Conference on Machine Learning, 5276-5285, 2018
3372018
Scalable coordinate descent approaches to parallel matrix factorization for recommender systems
HF Yu, CJ Hsieh, S Si, I Dhillon
2012 IEEE 12th international conference on data mining, 765-774, 2012
3122012
Coordinate descent method for large-scale l2-loss linear support vector machines.
KW Chang, CJ Hsieh, CJ Lin
Journal of Machine Learning Research 9 (7), 2008
2822008
Imagenet training in minutes
Y You, Z Zhang, CJ Hsieh, J Demmel, K Keutzer
Proceedings of the 47th International Conference on Parallel Processing, 1-10, 2018
2722018
A comparison of optimization methods and software for large-scale l1-regularized linear classification
GX Yuan, KW Chang, CJ Hsieh, CJ Lin
The Journal of Machine Learning Research 11, 3183-3234, 2010
2722010
Large batch optimization for deep learning: Training bert in 76 minutes
Y You, J Li, S Reddi, J Hseu, S Kumar, S Bhojanapalli, X Song, J Demmel, ...
arXiv preprint arXiv:1904.00962, 2019
265*2019
Efficient neural network robustness certification with general activation functions
H Zhang, TW Weng, PY Chen, CJ Hsieh, L Daniel
arXiv preprint arXiv:1811.00866, 2018
2622018
Visualbert: A simple and performant baseline for vision and language
LH Li, M Yatskar, D Yin, CJ Hsieh, KW Chang
arXiv preprint arXiv:1908.03557, 2019
2602019
Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks
WL Chiang, X Liu, S Si, Y Li, S Bengio, CJ Hsieh
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
2352019
Fast coordinate descent methods with variable selection for non-negative matrix factorization
CJ Hsieh, IS Dhillon
Proceeding of the 17th ACM SIGKDD international conference on Knowledge …, 2011
2312011
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
2082018
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
1982018
Large linear classification when data cannot fit in memory
HF Yu, CJ Hsieh, KW Chang, CJ Lin
ACM Transactions on Knowledge Discovery from Data (TKDD) 5 (4), 1-23, 2012
1972012
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