| Dive into deep learning A Zhang, ZC Lipton, M Li, AJ Smola arXiv preprint arXiv:2106.11342, 2021 | 731 | 2021 |
| Using deep learning to enhance cancer diagnosis and classification R Fakoor, F Ladhak, A Nazi, M Huber The 30th International Conference on Machine Learning (ICML 2013),WHEALTH …, 2013 | 523 | 2013 |
| Meta-Q-Learning R Fakoor, P Chaudhari, S Soatto, AJ Smola International Conference on Learning Representations (ICLR 2020), 2019 | 98 | 2019 |
| P3O: Policy-on Policy-off Policy Optimization R Fakoor, P Chaudhari, AJ Smola Proceedings of The 35th Uncertainty in Artificial Intelligence Conference …, 2020 | 39 | 2020 |
| An integrated cloud-based framework for mobile phone sensing R Fakoor, M Raj, A Nazi, M Di Francesco, SK Das Proceedings of the first edition of the MCC workshop on Mobile cloud …, 2012 | 33 | 2012 |
| Memory-augmented attention modelling for videos R Fakoor, A Mohamed, M Mitchell, SB Kang, P Kohli arXiv preprint arXiv:1611.02261, 2016 | 30 | 2016 |
| Fast, accurate, and simple models for tabular data via augmented distillation R Fakoor, JW Mueller, N Erickson, P Chaudhari, AJ Smola 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020 | 29 | 2020 |
| TraDE: Transformers for Density Estimation R Fakoor, P Chaudhari, J Mueller, AJ Smola arXiv preprint arXiv:2004.02441, 2020 | 17* | 2020 |
| Continuous doubly constrained batch reinforcement learning R Fakoor, JW Mueller, K Asadi, P Chaudhari, AJ Smola Advances in Neural Information Processing Systems 34, 11260-11273, 2021 | 15 | 2021 |
| Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality R Fakoor, X He, I Tashev, S Zarar NIPS 2017, Machine Learning for Audio Signal Processing workshop, 2017 | 14 | 2017 |
| Flexible Model Aggregation for Quantile Regression R Fakoor, T Kim, J Mueller, AJ Smola, RJ Tibshirani arXiv preprint arXiv:2103.00083, 2022 | 9* | 2022 |
| Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy R Fakoor, X He, I Tashev, S Zarar. IEEE International Conference on Acoustics, Speech and Signal Processing …, 2018 | 9 | 2018 |
| Differentiable Greedy Networks T Powers, R Fakoor, S Shakeri, A Sethy, A Kainth, ... arXiv preprint arXiv:1810.12464, 2018 | 7 | 2018 |
| Task-agnostic continual reinforcement learning: In praise of a simple baseline M Caccia, J Mueller, T Kim, L Charlin, R Fakoor arXiv preprint arXiv:2205.14495, 2022 | 6 | 2022 |
| DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning R Fakoor, P Chaudhari, A Smola | 3 | 2020 |
| Direct Optimization of F-measure for Retrieval-based Personal Question Answering R Fakoor, A Kainth, S Shakeri, C Winestock, A Mohamed, R Sarikaya IEEE Spoken Language Technology, 2018 | 2 | 2018 |
| Deep Attribute-based Zero-shot Learning with Layer-specific Regularizers R Fakoor, M Bansal, MR Walter NIPS 2015 , Transfer and Multi-Task Learning Workshop, 2015 | 2 | 2015 |
| Improving tractability of POMDPs by separation of decision and perceptual processes R Fakoor, M Huber 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2012 | 2 | 2012 |
| A Sampling-Based Approach to Reducing the Complexity of Continuous State Space POMDPs by Decomposition into Coupled Perceptual and Decision Processes R Fakoor, M Huber 11th International Conference on Machine Learning and Applications (ICMLA), 2012 | 2 | 2012 |
| Faster deep reinforcement learning with slower online network K Asadi, R Fakoor, O Gottesman, T Kim, ML Littman, A Smola 36th Conference on Neural Information Processing Systems (NeurIPS 2022)., 2022 | 1* | 2022 |
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