Xi Wu
Xi Wu
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Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
N Papernot, P McDaniel, X Wu, S Jha, A Swami
Security and Privacy (SP), 2016 IEEE Symposium on, 582-597, 2016
Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics
X Wu, F Li, A Kumar, K Chaudhuri, S Jha, JF Naughton
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
A Methodology for Modeling Model-Inversion Attacks
X Wu, M Fredrikson, S Jha, JF Naughton
Computer Security Foundations Symposium (CSF), 2016 IEEE 29th, 355-370, 2016
Objective metrics and gradient descent algorithms for adversarial examples in machine learning
U Jang, X Wu, S Jha
Proceedings of the 33rd Annual Computer Security Applications Conference …, 2017
Atom: Robustifying out-of-distribution detection using outlier mining
J Chen, Y Li, X Wu, Y Liang, S Jha
Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021
COREMU: a Scalable and Portable Parallel Full-System Emulator
Z Wang, R Liu, Y Chen, X Wu, H Chen, W Zhang, B Zang
ACM SIGPLAN Notices 46 (8), 213-222, 2011
Concise Explanations for Neural Networks using Adversarial Training
P Chalasani, J Chen, S Jha, X Wu
arXiv preprint arXiv:1810.06583, 2018
Robust out-of-distribution detection for neural networks
J Chen, Y Li, X Wu, Y Liang, S Jha
arXiv preprint arXiv:2003.09711, 2020
Weak Compositions and Their Applications to Polynomial Lower Bounds for Kernelization
D Hermelin, X Wu
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012
Robust attribution regularization
J Chen, X Wu, V Rastogi, Y Liang, S Jha
Advances in Neural Information Processing Systems 32, 2019
A Completeness Theory for Polynomial (Turing) Kernelization
D Hermelin, S Kratsch, K Sołtys, M Wahlström, X Wu
Algorithmica 71 (3), 702-730, 2015
From Speculation to Security: Practical and Efficient Information Flow Tracking using Speculative Hardware
H Chen, X Wu, L Yuan, B Zang, P Yew, FT Chong
Computer Architecture, 2008. ISCA'08. 35th International Symposium on, 401-412, 2008
Detecting errors and estimating accuracy on unlabeled data with self-training ensembles
J Chen, F Liu, B Avci, X Wu, Y Liang, S Jha
Advances in Neural Information Processing Systems 34, 14980-14992, 2021
Control Flow Obfuscation with Information Flow Tracking
H Chen, L Yuan, X Wu, B Zang, B Huang, P Yew
Proceedings of the 42nd Annual IEEE/ACM International Symposium on …, 2009
Diff: a relational interface for large-scale data explanation
F Abuzaid, P Kraft, S Suri, E Gan, E Xu, A Shenoy, A Ananthanarayan, ...
Proceedings of the VLDB Endowment 12 (4), 419-432, 2018
Uncertainty Aware Query Execution Time Prediction
W Wu, X Wu, H Hacigümüş, JF Naughton
Proceedings of the VLDB Endowment 7 (14), 1857-1868, 2014
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks
J Chen, X Wu, Y Liang, S Jha
arXiv preprint arXiv:1805.07816, 2018
Tuple-oriented compression for large-scale mini-batch stochastic gradient descent
F Li, L Chen, Y Zeng, A Kumar, X Wu, JF Naughton, JM Patel
Proceedings of the 2019 International Conference on Management of Data, 1517 …, 2019
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
X Wu, U Jang, J Chen, L Chen, S Jha
Proceedings of the 35th International Conference on Machine Learning 80 …, 2018
Revisiting Differentially Private Regression: Lessons from Learning Theory and Their Consequences
X Wu, M Fredrikson, W Wu, S Jha, JF Naughton
arXiv preprint arXiv:1512.06388, 2015
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