Tribhuvanesh Orekondy
Tribhuvanesh Orekondy
Qualcomm AI Research
Verified email at qti.qualcomm.com - Homepage
Title
Cited by
Cited by
Year
Knockoff Nets: Stealing Functionality of Black-Box Models
T Orekondy, B Schiele, M Fritz
Computer Vision and Pattern Recognition (CVPR), 2019
802019
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images
T Orekondy, B Schiele, M Fritz
The IEEE International Conference on Computer Vision (ICCV), 2017
522017
Connecting Pixels to Privacy and Utility: Automatic Redaction of Private Information in Images
T Orekondy, M Fritz, B Schiele
Computer Vision and Pattern Recognition (CVPR), 2018
332018
Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks
T Orekondy, B Schiele, M Fritz
International Conference on Learning Representations (ICLR), 2020
17*2020
Gradient-Leaks: Understanding Deanonymization in Federated Learning
T Orekondy, SJ Oh, Y Zhang, B Schiele, M Fritz
NeurIPS Workshop on Federated Learning for Data Privacy and Confidentiality, 2019
11*2019
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning
T Orekondy, SJ Oh, Y Zhang, B Schiele, M Fritz
arXiv preprint arXiv:1805.05838, 2018
52018
Gs-wgan: A gradient-sanitized approach for learning differentially private generators
D Chen, T Orekondy, M Fritz
arXiv preprint arXiv:2006.08265, 2020
32020
Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries
S Rahimian, T Orekondy, M Fritz
arXiv preprint arXiv:2009.00395, 2020
12020
Differential Privacy Defenses and Sampling Attacks for Membership Inference
S Rahimian, T Orekondy, M Fritz
PriML Workshop (PriML) 13, 2019
12019
InfoScrub: Towards Attribute Privacy by Targeted Obfuscation
HP Wang, T Orekondy, M Fritz
arXiv preprint arXiv:2005.10329, 2020
2020
HADES: Hierarchical Approximate Decoding for Structured Prediction
T Orekondy
ETH-Zürich, 2015
2015
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Articles 1–11