| Learning causal structures using regression invariance AE Ghassami, S Salehkaleybar, N Kiyavash, K Zhang arXiv preprint arXiv:1705.09644, 2017 | 28 | 2017 |
| Budgeted experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash, E Bareinboim International Conference on Machine Learning, 1724-1733, 2018 | 27 | 2018 |
| Fairness in supervised learning: An information theoretic approach AE Ghassami, S Khodadadian, N Kiyavash 2018 IEEE International Symposium on Information Theory (ISIT), 176-180, 2018 | 23 | 2018 |
| Sneak-peek: High speed covert channels in data center networks R Tahir, MT Khan, X Gong, A Ahmed, AE Ghassami, H Kazmi, M Caesar, ... INFOCOM 2016-The 35th Annual IEEE International Conference on Computer …, 2016 | 23 | 2016 |
| Schedule-based side-channel attack in fixed-priority real-time systems CY Chen, AE Ghassami, S Nagy, MK Yoon, S Mohan, N Kiyavash, ... Proceedings of the IEEE Workshop on Security and Dependability of Critical …, 2016 | 19 | 2016 |
| Capacity limit of queueing timing channel in shared FCFS schedulers AE Ghassami, X Gong, N Kiyavash 2015 IEEE International Symposium on Information Theory (ISIT), 789-793, 2015 | 16 | 2015 |
| Counting and sampling from Markov equivalent DAGs using clique trees AE Ghassami, S Salehkaleybar, N Kiyavash, K Zhang Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3664-3671, 2019 | 11 | 2019 |
| Multi-domain causal structure learning in linear systems AE Ghassami, N Kiyavash, B Huang, K Zhang Advances in neural information processing systems 31, 6266, 2018 | 10 | 2018 |
| On the role of sparsity and dag constraints for learning linear dags I Ng, AE Ghassami, K Zhang arXiv preprint arXiv:2006.10201, 2020 | 7 | 2020 |
| A covert queueing channel in FCFS schedulers AE Ghassami, N Kiyavash IEEE Transactions on Information Forensics and Security 13 (6), 1551-1563, 2018 | 6 | 2018 |
| Interaction information for causal inference: The case of directed triangle AE Ghassami, N Kiyavash 2017 IEEE International Symposium on Information Theory (ISIT), 1326-1330, 2017 | 6 | 2017 |
| A reconnaissance attack mechanism for fixed-priority real-time systems CY Chen, AE Ghassami, S Mohan, N Kiyavash, RB Bobba, R Pellizzoni, ... arXiv preprint arXiv:1705.02561, 2017 | 6 | 2017 |
| Interventional experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash arXiv preprint arXiv:1910.05651, 2019 | 5 | 2019 |
| REORDER: Securing Dynamic-Priority Real-Time Systems Using Schedule Obfuscation CY Chen, M Hasan, AE Ghassami, S Mohan, N Kiyavash arXiv preprint arXiv:1806.01393, 2018 | 5 | 2018 |
| Optimal experiment design for causal discovery from fixed number of experiments AE Ghassami, S Salehkaleybar, N Kiyavash arXiv preprint arXiv:1702.08567, 2017 | 5 | 2017 |
| Message partitioning and limited auxiliary randomness: Alternatives to Honey Encryption AE Ghassami, D Cullina, N Kiyavash 2016 IEEE International Symposium on Information Theory (ISIT), 1371-1375, 2016 | 5 | 2016 |
| Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs AE Ghassami, A Yang, N Kiyavash, K Zhang 37th International Conference on Machine Learning (ICML), 2020 | 4* | 2020 |
| A covert queueing channel in round robin schedulers AE Ghassami, A Yekkehkhany, N Kiyavash arXiv preprint arXiv:1701.08883, 2017 | 4 | 2017 |
| Model-Augmented Conditional Mutual Information Estimation for Feature Selection A Yang, AE Ghassami, M Raginsky, N Kiyavash, E Rosenbaum 36th Conference on Uncertainty in Artificial Intelligence (UAI) 124, 2020 | 2* | 2020 |
| Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables. S Salehkaleybar, AE Ghassami, N Kiyavash, K Zhang Journal of Machine Learning Research 21 (39), 1-24, 2020 | 2 | 2020 |
Negar KiyavashÉcole polytechnique fédérale de Lausanne (EPFL)Verified email at epfl.ch
