| Stopwasting my gradients: Practical svrg R Babanezhad Harikandeh, MO Ahmed, A Virani, M Schmidt, J Konečný, ... Advances in Neural Information Processing Systems 28, 2015 | 165 | 2015 |
| Non-uniform stochastic average gradient method for training conditional random fields M Schmidt, R Babanezhad, M Ahmed, A Defazio, A Clifton, A Sarkar artificial intelligence and statistics, 819-828, 2015 | 101 | 2015 |
| Power line communications for low-voltage power grid tomography MO Ahmed, L Lampe IEEE Transactions on Communications 61 (12), 5163-5175, 2013 | 95 | 2013 |
| Human intracranial EEG quantitative analysis and automatic feature learning for epileptic seizure prediction R Hussein, MO Ahmed, R Ward, ZJ Wang, L Kuhlmann, Y Guo arXiv preprint arXiv:1904.03603, 2019 | 50 | 2019 |
| Do we need “harmless” Bayesian optimization and “first-order” Bayesian optimization MO Ahmed, B Shahriari, M Schmidt NIPS BayesOpt 5, 21, 2016 | 36 | 2016 |
| Power line network topology inference using frequency domain reflectometry MO Ahmed, L Lampe 2012 IEEE International Conference on Communications (ICC), 3419-3423, 2012 | 36 | 2012 |
| Power grid topology inference using power line communications L Lampe, MO Ahmed 2013 IEEE International Conference on Smart Grid Communications …, 2013 | 33 | 2013 |
| Combining Bayesian optimization and Lipschitz optimization MO Ahmed, S Vaswani, M Schmidt Machine Learning 109, 79-102, 2020 | 25 | 2020 |
| Towards Better Selective Classification L Feng, MO Ahmed, H Hajimirsadeghi, AH Abdi The Eleventh International Conference on Learning Representations, 2023 | 22* | 2023 |
| Meta Temporal Point Processes W Bae, MO Ahmed, F Tung, GL Oliveira The Eleventh International Conference on Learning Representations, 2023 | 17 | 2023 |
| Parametric and nonparametric methods for power line network topology inference MO Ahmed, L Lampe 2012 IEEE International Symposium on Power Line Communications and Its …, 2012 | 17 | 2012 |
| Latent Bottlenecked Attentive Neural Processes L Feng, H Hajimirsadeghi, Y Bengio, MO Ahmed The Eleventh International Conference on Learning Representations, 2023 | 16 | 2023 |
| Point process flows N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ... arXiv preprint arXiv:1910.08281, 2019 | 15 | 2019 |
| System and method for generative model for stochastic point processes N Mehrasa, AA Jyothi, T Durand, J He, M Gregory, M Ahmed, M Brubaker US Patent App. 16/685,327, 2020 | 14 | 2020 |
| Mirage: Machine learning-based modeling of identical replicas of the jetson agx embedded platform HA Abdelhafez, H Halawa, MO Ahmed, K Pattabiraman, M Ripeanu 2021 IEEE/ACM Symposium on Edge Computing (SEC), 26-40, 2021 | 8 | 2021 |
| Attention as an RNN L Feng, F Tung, H Hajimirsadeghi, MO Ahmed, Y Bengio, G Mori arXiv preprint arXiv:2405.13956, 2024 | 5 | 2024 |
| METAL: Towards Multilingual Meta-Evaluation R Hada, V Gumma, M Ahmed, K Bali, S Sitaram arXiv preprint arXiv:2404.01667, 2024 | 3 | 2024 |
| Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classification J Monteiro, MO Ahmed, H Hajimirsadeghi, G Mori Uncertainty in Artificial Intelligence, 1381-1391, 2022 | 3 | 2022 |
| Not too close and not too far: Enforcing monotonicity requires penalizing the right points J Monteiro, MO Ahmed, H Hajimirsadeghi, G Mori eXplainable AI approaches for debugging and diagnosis., 2021 | 3 | 2021 |
| Decentralized, adaptive, look-ahead particle filtering MO Ahmed, PT Bibalan, N de Freitas, S Fauvel arXiv preprint arXiv:1203.2394, 2012 | 3 | 2012 |
Hossein HajimirsadeghiPhD, Computer Science, Borealis AIEmail confirmado em sfu.ca
