| Byzantine-robust Federated Machine Learning Through Adaptive Model Averaging L Muñoz-González, KT Co, EC Lupu arXiv preprint arXiv:1909.05125, 2019 | 217 | 2019 |
| Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks KT Co, L Munoz Gonzalez, S De Maupeou, E Lupu 26th ACM SIGSAC Conference on Computer and Communications Security (CCS 2019), 2019 | 54 | 2019 |
| Object Removal Attacks on LiDAR-based 3D Object Detectors Z Hau, KT Co, S Demetriou, EC Lupu NDSS 2021: Automotive and Autonomous Vehicle Security (AutoSec), 2021 | 37 | 2021 |
| Universal Adversarial Robustness of Texture and Shape-Biased Models KT Co, L Muñoz-González, L Kanthan, B Glocker, EC Lupu 28th IEEE International Conference on Image Processing (ICIP 2021), 2019 | 11 | 2019 |
| Robustness and Transferability of Universal Attacks on Compressed Models AG Matachana, KT Co, L Muñoz-González, D Martinez, EC Lupu AAAI 2021: Towards Robust, Secure, and Efficient Machine Learning, 2020 | 9 | 2020 |
| Bayesian Optimization for Black-Box Evasion of Machine Learning Systems KT Co Imperial College London, 2017 | 9* | 2017 |
| Jacobian regularization for mitigating universal adversarial perturbations KT Co, DM Rego, EC Lupu International Conference on Artificial Neural Networks, 202-213, 2021 | 7 | 2021 |
| Byzantine-robust federated machine learning through adaptive model averaging. arXiv 2019 L Muñoz-González, KT Co, EC Lupu arXiv preprint arXiv:1909.05125, 0 | 7 | |
| Challenges and Advances in Adversarial Machine Learning L Muñoz-González, J Carnerero-Cano, KT Co, EC Lupu Resilience and Hybrid Threats: Security and Integrity for the Digital World …, 2019 | 5 | 2019 |
| Sensitivity of Deep Convolutional Networks to Gabor Noise KT Co, L Muñoz-González, EC Lupu ICML 2019: On Identifying and Understanding Deep Learning Phenomena, 2019 | 5 | 2019 |
| Real-time detection of practical universal adversarial perturbations KT Co, L Muñoz-González, L Kanthan, EC Lupu arXiv preprint arXiv:2105.07334, 2021 | 4* | 2021 |
| HA-Grid: Security Aware Hazard Analysis for Smart Grids L Castiglione, Z Hau, P Ge, K Co, L Munoz Gonzalez, F Teng, E Lupu 13th IEEE International Conference on Communications, Control, and Computing …, 2022 | 3 | 2022 |
| Universal Adversarial perturbations to understand robustness of texture vs. shape-biased training KT Co, L Munoz-González, L Kanthan, B Glocker, EC Lupu arXiv preprint arXiv:1911.10364, 2019 | 3 | 2019 |
| Jacobian Ensembles Improve Robustness Trade-Offs to Adversarial Attacks KT Co, D Martinez-Rego, Z Hau, EC Lupu International Conference on Artificial Neural Networks, 680-691, 2022 | 2 | 2022 |
| Understanding and Mitigating Universal Adversarial Perturbations for Computer Vision Neural Networks KT Co Imperial College London, 2023 | | 2023 |
Emil LupuProfessor of Computer SystemsПотвърден имейл адрес: imperial.ac.uk
