| On the (im) practicality of adversarial perturbation for image privacy A Rajabi, RB Bobba, M Rosulek, C Wright, W Feng Proceedings on Privacy Enhancing Technologies, 2021 | 46 | 2021 |
| Sampling from Complex Networks with high Community Structures M Salehi, HR Rabiee, A Rajabi Chaos: An Interdisciplinary Journal of Nonlinear Science 22, 2012 | 37 | 2012 |
| Toward adversarial robustness by diversity in an ensemble of specialized deep neural networks M Abbasi, A Rajabi, C Gagné, RB Bobba Advances in Artificial Intelligence: 33rd Canadian Conference on Artificial …, 2020 | 17 | 2020 |
| The trojan detection challenge M Mazeika, D Hendrycks, H Li, X Xu, S Hough, A Zou, A Rajabi, Q Yao, ... NeurIPS 2022 Competition Track, 279-291, 2022 | 15 | 2022 |
| Dani: A fast diffusion aware network inference algorithm M Ramezani, HR Rabiee, M Tahani, A Rajabi arXiv preprint arXiv:1706.00941, 2017 | 13 | 2017 |
| Controlling over-generalization and its effect on adversarial examples generation and detection M Abbasi, A Rajabi, AS Mozafari, RB Bobba, C Gagne arXiv preprint arXiv:1808.08282, 2018 | 8 | 2018 |
| Resilience against data manipulation in distributed synchrophasor-based mode estimation A Rajabi, RB Bobba IEEE Transactions on Smart Grid 12 (4), 3538-3547, 2021 | 6 | 2021 |
| Toward metrics for differentiating out-of-distribution sets M Abbasi, C Shui, A Rajabi, C Gagné, RB Bobba ECAI 2020, 929-936, 2020 | 6 | 2020 |
| Towards dependable deep convolutional neural networks (cnns) with out-distribution learning M Abbasi, A Rajabi, C Gagné, RB Bobba arXiv preprint arXiv:1804.08794, 2018 | 6 | 2018 |
| A resilient algorithm for power system mode estimation using synchrophasors A Rajabi, RB Bobba Proceedings of the 2nd Annual Industrial Control System Security Workshop, 23-29, 2016 | 6 | 2016 |
| Trojan horse training for breaking defenses against backdoor attacks in deep learning A Rajabi, B Ramasubramanian, R Poovendran arXiv preprint arXiv:2203.15506, 2022 | 4 | 2022 |
| LDL: A defense for label-based membership inference attacks A Rajabi, D Sahabandu, L Niu, B Ramasubramanian, R Poovendran Proceedings of the 2023 ACM Asia Conference on Computer and Communications …, 2023 | 3 | 2023 |
| Adversarial Profiles: Detecting Out-Distribution & Adversarial Samples in Pre-trained CNNs A Rajabi, RB Bobba arXiv preprint arXiv:2011.09123, 2020 | 3 | 2020 |
| FedGame: a game-theoretic defense against backdoor attacks in federated learning J Jia, Z Yuan, D Sahabandu, L Niu, A Rajabi, B Ramasubramanian, B Li, ... Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors D Sahabandu, X Xu, A Rajabi, L Niu, B Ramasubramanian, B Li, ... arXiv preprint arXiv:2402.08695, 2024 | 1 | 2024 |
| MDTD: A Multi-Domain Trojan Detector for Deep Neural Networks A Rajabi, S Asokraj, F Jiang, L Niu, B Ramasubramanian, J Ritcey, ... Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications …, 2023 | 1 | 2023 |
| Privacy-Preserving Reinforcement Learning Beyond Expectation A Rajabi, B Ramasubramanian, A Al Maruf, R Poovendran 2022 IEEE 61st Conference on Decision and Control (CDC), 4706-4713, 2022 | 1 | 2022 |
| False data detection in distributed oscillation mode estimation using hierarchical k-means A Rajabi, RB Bobba 2019 IEEE International Conference on Communications, Control, and Computing …, 2019 | 1 | 2019 |
| Controlling Over-generalization and its Effect on Adversarial Examples Detection and Generation M Abbasi, A Rajabi, AS Mozafari, RB Bobba, C Gagné | 1 | 2018 |
| INVESTIGATION ON SOME BIOLOGICAL CHARACTERISTIC IN LEUCISCUS CEPHALUS AT BABOLRUD RIVER, MAZANDARAN PROVINCE AA ASHJA, E RAD, A RAJABI JOURNAL OF MARINE SCIENCE AND TECHNOLOGY RESEARCH 5 (4), 19-32, 2011 | 1 | 2011 |
Rakesh B BobbaOregon State University在 oregonstate.edu 的电子邮件经过验证
