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 | 253 | 2011 |
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 | 54 | 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 | 45 | 2019 |
Sequential fair allocation: Achieving the optimal envy-efficiency tradeoff curve SR Sinclair, S Banerjee, CL Yu ACM SIGMETRICS Performance Evaluation Review 50 (1), 95-96, 2022 | 35 | 2022 |
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 | 33 | 2017 |
Estimating the total treatment effect in randomized experiments with unknown network structure CL Yu, EM Airoldi, C Borgs, JT Chayes Proceedings of the National Academy of Sciences 119 (44), e2208975119, 2022 | 28 | 2022 |
Sukin Sim, Arshpreet Singh, Ingrid Strandberg, Jay Soni, Antal Száva, Slimane Thabet, Rodrigo A V Bergholm, J Izaac, M Schuld, C Gogolin, S Ahmed, V Ajith, MS Alam, ... Vargas-Hernández, Trevor Vincent, Nicola Vitucci, Maurice Weber, David …, 2022 | 28 | 2022 |
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 | 27* | 2019 |
Computing the stationary distribution locally CE Lee, A Ozdaglar, D Shah Advances in Neural Information Processing Systems 26, 2013 | 27 | 2013 |
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 | 24 | 2020 |
Reducing crowdsourcing to graphon estimation, statistically D Shah, C Lee International Conference on Artificial Intelligence and Statistics, 1741-1750, 2018 | 22 | 2018 |
Sequential fair allocation of limited resources under stochastic demands SR Sinclair, G Jain, S Banerjee, CL Yu arXiv preprint arXiv:2011.14382, 2020 | 21 | 2020 |
Iterative collaborative filtering for sparse noisy tensor estimation D Shah, CL Yu 2019 IEEE International Symposium on Information Theory (ISIT), 41-45, 2019 | 19 | 2019 |
Solving systems of linear equations: Locally and asynchronously CE Lee, AE Ozdaglar, D Shah Computing Research Repository, 2014 | 19 | 2014 |
Staggered rollout designs enable causal inference under interference without network knowledge M Cortez, M Eichhorn, C Yu Advances in Neural Information Processing Systems 35, 7437-7449, 2022 | 17 | 2022 |
Nonparametric contextual bandits in metric spaces with unknown metric N Wanigasekara, C Yu Advances in Neural Information Processing Systems 32, 2019 | 17 | 2019 |
Exploiting neighborhood interference with low-order interactions under unit randomized design M Cortez-Rodriguez, M Eichhorn, CL Yu Journal of Causal Inference 11 (1), 20220051, 2023 | 11 | 2023 |
Overcoming the long horizon barrier for sample-efficient reinforcement learning with latent low-rank structure T Sam, Y Chen, CL Yu Proceedings of the ACM on Measurement and Analysis of Computing Systems 7 (2 …, 2023 | 11 | 2023 |
Iterative collaborative filtering for sparse matrix estimation C Borgs, JT Chayes, D Shah, CL Yu Operations Research 70 (6), 3143-3175, 2022 | 11 | 2022 |
Unifying framework for crowd-sourcing via graphon estimation CE Lee, D Shah arXiv preprint arXiv:1703.08085, 2017 | 11 | 2017 |