| Budgeted experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash, E Bareinboim International Conference on Machine Learning, 2018 | 55 | 2018 |
| Learning causal structures using regression invariance AE Ghassami, S Salehkaleybar, N Kiyavash, K Zhang Neural Information Processing Systems, 2017 | 49 | 2017 |
| cuPC: CUDA-based Parallel PC Algorithm for Causal Structure Learning on GPU B Zare, F Jafarinejad, M Hashemi, S Salehkaleybar IEEE transactions on Parallel and Distributed Systems, 2018 | 24* | 2018 |
| 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, 39:1-39:24, 2020 | 20 | 2020 |
| One-shot federated learning: theoretical limits and algorithms to achieve them S Salehkaleybar, A Sharifnassab, SJ Golestani Journal of Machine Learning Research, 2021 | 19* | 2021 |
| 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 | 19 | 2019 |
| Deep-learning-based blind recognition of channel code parameters over candidate sets under AWGN and multi-path fading conditions S Dehdashtian, M Hashemi, S Salehkaleybar IEEE Wireless Communications Letters 10 (5), 1041-1045, 2021 | 12 | 2021 |
| Distributed Voting/Ranking with Optimal Number of States per Node S Salehkaleybar, A Sharif-Nassab, SJ Golestani IEEE transactions on Signal and Information Processing over Networks, 2015 | 11 | 2015 |
| Order optimal one-shot distributed learning A Sharifnassab, S Salehkaleybar, SJ Golestani Neural Information Processing Systems, 2019 | 10 | 2019 |
| gim: Gpu accelerated ris-based influence maximization algorithm S Shahrouz, S Salehkaleybar, M Hashemi IEEE Transactions on Parallel and Distributed Systems 32 (10), 2386-2399, 2021 | 8 | 2021 |
| LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments A AhmadiTeshnizi, S Salehkaleybar, N Kiyavash International Conference on Machine Learning, 2020 | 8 | 2020 |
| Interventional experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash arXiv preprint arXiv:1910.05651, 2019 | 8 | 2019 |
| Bounds on over-parameterization for guaranteed existence of descent paths in shallow ReLU networks A Sharifnassab, S Salehkaleybar, SJ Golestani International conference on learning representations, 2020 | 7 | 2020 |
| A periodic jump-based rendezvous algorithm in cognitive radio networks S Salehkaleybar, MR Pakravan Computer Communications 79, 66-77, 2016 | 7 | 2016 |
| Seedless graph matching via tail of degree distribution for correlated erdos-renyi graphs M Bozorg, S Salehkaleybar, M Hashemi arXiv preprint arXiv:1907.06334, 2019 | 6 | 2019 |
| Identifying nonlinear 1-step causal influences in presence of latent variables S Salehkaleybar, J Etesami, N Kiyavash 2017 IEEE International Symposium on Information Theory (ISIT), 1341-1345, 2017 | 6 | 2017 |
| Optimal experiment design for causal discovery from fixed number of experiments AE Ghassami, S Salehkaleybar, N Kiyavash arXiv preprint arXiv:1702.08567, 2017 | 6 | 2017 |
| QoS-aware joint policies in cognitive radio networks S Salehkaleybar, SA Majd, MR Pakravan 2011 7th International Wireless Communications and Mobile Computing …, 2011 | 6 | 2011 |
| ParaLiNGAM: parallel causal structure learning for linear non-gaussian acyclic models A Shahbazinia, S Salehkaleybar, M Hashemi Journal of Parallel and Distributed Computing, 2023 | 4 | 2023 |
| Active learning of causal structures with deep reinforcement learning A Amirinezhad, S Salehkaleybar, M Hashemi Neural Networks 154, 22-30, 2022 | 4 | 2022 |
Negar KiyavashÉcole polytechnique fédérale de Lausanne (EPFL)Verified email at epfl.ch
