Jasjeet Dhaliwal
Jasjeet Dhaliwal
Center for Advanced Machine Learning, Symantec
Verified email at symantec.com
Title
Cited by
Cited by
Year
Fence
K Kim
US Patent App. 10/225,277, 2003
132003
Gradient similarity: An explainable approach to detect adversarial attacks against deep learning
J Dhaliwal, S Shintre
arXiv preprint arXiv:1806.10707, 2018
32018
Verifying that the influence of a user data point has been removed from a machine learning classifier
S Shintre, J Dhaliwal
US Patent 10,225,277, 2019
22019
Making Machine Learning Forget
S Shintre, KA Roundy, J Dhaliwal
Annual Privacy Forum, 72-83, 2019
12019
Deep Detector Health Management under Adversarial Campaigns
J Echauz, K Kenemer, S Hussein, J Dhaliwal, S Shintre, S Grzonkowski, ...
arXiv preprint arXiv:1911.08090, 2019
2019
Compressive Recovery Defense: A Defense Framework for and norm attacks.
J Dhaliwal, K Hambrook
2019
Adversarial Campaign Mitigation via ROC-Centric Prognostics
J Echauz, K Kenemer, S Hussein, J Dhaliwal, S Shintre, S Grzonkowski, ...
Annual Conference of the PHM Society 11 (1), 2019
2019
Verifying that the influence of a user data point has been removed from a machine learning classifier
S Shintre, J Dhaliwal
US Patent 10,397,266, 2019
2019
Recovery Guarantees for Compressible Signals with Adversarial Noise
J Dhaliwal, K Hambrook
arXiv preprint arXiv:1907.06565, 2019
2019
Utility Preserving Secure Private Data Release
J Dhaliwal, G So, A Parker-Wood, M Beck
arXiv preprint arXiv:1901.09858, 2019
2019
Neural Machine Translation with LSTM’s
J Dhaliwal
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Articles 1–11