| Peer effects and stability in matching markets E Bodine-Baron, C Lee, A Chong, B Hassibi, A Wierman International Symposium on Algorithmic Game Theory, 117-129, 2011 | 196 | 2011 |
| Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing WE Allen, H Altae-Tran, J Briggs, X Jin, G McGee, A Shi, R Raghavan, ... Nature human behaviour 4 (9), 972-982, 2020 | 84 | 2020 |
| Blind regression: Nonparametric regression for latent variable models via collaborative filtering D Song, CE Lee, Y Li, D Shah Advances in Neural Information Processing Systems 29, 2016 | 45 | 2016 |
| Blind regression: Nonparametric regression for latent variable models via collaborative filtering D Song, CE Lee, Y Li, D Shah Advances in Neural Information Processing Systems 29, 2016 | 45 | 2016 |
| Adaptive discretization for episodic reinforcement learning in metric spaces SR Sinclair, S Banerjee, CL Yu Proceedings of the ACM on Measurement and Analysis of Computing Systems 3 (3 …, 2019 | 36 | 2019 |
| Thy friend is my friend: Iterative collaborative filtering for sparse matrix estimation C Borgs, J Chayes, CE Lee, D Shah Advances in neural information processing systems 30, 2017 | 29 | 2017 |
| Modulating androgen receptor-driven transcription in prostate cancer with selective CDK9 inhibitors A Richters, SK Doyle, DB Freeman, C Lee, BS Leifer, S Jagannathan, ... Cell Chemical Biology 28 (2), 134-147. e14, 2021 | 26 | 2021 |
| Computing the stationary distribution locally CE Lee, A Ozdaglar, D Shah Advances in Neural Information Processing Systems 26, 2013 | 21 | 2013 |
| Nearest neighbors for matrix estimation interpreted as blind regression for latent variable model Y Li, D Shah, D Song, CL Yu IEEE Transactions on Information Theory 66 (3), 1760-1784, 2019 | 20* | 2019 |
| Reducing crowdsourcing to graphon estimation, statistically D Shah, C Lee International Conference on Artificial Intelligence and Statistics, 1741-1750, 2018 | 17 | 2018 |
| Solving systems of linear equations: Locally and asynchronously CE Lee, AE Ozdaglar, D Shah arXiv preprint arXiv:1411.2647, 2014 | 17 | 2014 |
| Adaptive discretization for model-based reinforcement learning S Sinclair, T Wang, G Jain, S Banerjee, C Yu Advances in Neural Information Processing Systems 33, 3858-3871, 2020 | 16 | 2020 |
| Iterative collaborative filtering for sparse noisy tensor estimation D Shah, CL Yu 2019 IEEE International Symposium on Information Theory (ISIT), 41-45, 2019 | 13 | 2019 |
| Unifying framework for crowd-sourcing via graphon estimation CE Lee, D Shah arXiv preprint arXiv:1703.08085, 2017 | 11 | 2017 |
| Nonparametric contextual bandits in metric spaces with unknown metric N Wanigasekara, C Yu Advances in Neural Information Processing Systems 32, 2019 | 10 | 2019 |
| Asynchronous approximation of a single component of the solution to a linear system CE Lee, A Ozdaglar, D Shah arXiv preprint arXiv:1411.2647, 2014 | 9 | 2014 |
| Iterative collaborative filtering for sparse matrix estimation C Borgs, JT Chayes, D Shah, CL Yu Operations Research, 2021 | 7 | 2021 |
| Sequential fair allocation of limited resources under stochastic demands SR Sinclair, G Jain, S Banerjee, CL Yu arXiv preprint arXiv:2011.14382, 2020 | 6 | 2020 |
| Sequential fair allocation: Achieving the optimal envy-efficiency tradeoff curve SR Sinclair, S Banerjee, CL Yu Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint …, 2022 | 5 | 2022 |
| Approximating the Stationary Probability of a Single State in a Markov chain CE Lee, A Ozdaglar, D Shah arXiv preprint arXiv:1312.1986, 2013 | 4 | 2013 |
Devavrat ShahMassachusetts Institute of TechnologyVerified email at mit.edu
