| Budgeted experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash, E Bareinboim International Conference on Machine Learning, 2018 | 68 | 2018 |
| Learning causal structures using regression invariance AE Ghassami, S Salehkaleybar, N Kiyavash, K Zhang Neural Information Processing Systems, 2017 | 65 | 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 | 35* | 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 | 34 | 2020 |
| One-shot federated learning: theoretical limits and algorithms to achieve them S Salehkaleybar, A Sharifnassab, SJ Golestani Journal of Machine Learning Research, 2021 | 29* | 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 | 24 | 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 | 21 | 2021 |
| Order optimal one-shot distributed learning A Sharifnassab, S Salehkaleybar, SJ Golestani Neural Information Processing Systems, 2019 | 14 | 2019 |
| Stochastic second-order methods improve best-known sample complexity of sgd for gradient-dominated functions S Masiha, S Salehkaleybar, N He, N Kiyavash, P Thiran Advances in Neural Information Processing Systems 35, 10862-10875, 2022 | 13 | 2022 |
| 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 | 13 | 2015 |
| Causal imitative model for autonomous driving MR Samsami, M Bahari, S Salehkaleybar, A Alahi arXiv preprint arXiv:2112.03908, 2021 | 12 | 2021 |
| Interventional experiment design for causal structure learning AE Ghassami, S Salehkaleybar, N Kiyavash arXiv preprint arXiv:1910.05651, 2019 | 11 | 2019 |
| 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 | 11 | 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 | 10 | 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 | 10 | 2020 |
| Active learning of causal structures with deep reinforcement learning A Amirinezhad, S Salehkaleybar, M Hashemi Neural Networks 154, 22-30, 2022 | 9 | 2022 |
| 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, 2019 | 9 | 2019 |
| Momentum-Based Policy Gradient with Second-Order Information S Salehkaleybar, S Khorasani, N Kiyavash, N He, P Thiran arXiv preprint arXiv:2205.08253, 2022 | 8 | 2022 |
| A periodic jump-based rendezvous algorithm in cognitive radio networks S Salehkaleybar, MR Pakravan Computer Communications 79, 66-77, 2016 | 8 | 2016 |
| ParaLiNGAM: Parallel causal structure learning for linear non-Gaussian acyclic models A Shahbazinia, S Salehkaleybar, M Hashemi Journal of Parallel and Distributed Computing 176, 114-127, 2023 | 7 | 2023 |
Negar KiyavashÉcole polytechnique fédérale de Lausanne (EPFL)epfl.ch üzerinde doğrulanmış e-posta adresine sahip
