| Top challenges from the first practical online controlled experiments summit S Gupta, R Kohavi, D Tang, Y Xu, R Andersen, E Bakshy, N Cardin, ... ACM SIGKDD Explorations Newsletter 21 (1), 20-35, 2019 | 116 | 2019 |
| Multiple randomization designs P Bajari, B Burdick, GW Imbens, L Masoero, J McQueen, T Richardson, ... arXiv preprint arXiv:2112.13495, 2021 | 53 | 2021 |
| Megaman: Scalable manifold learning in python J McQueen, M Meilă, J VanderPlas, Z Zhang Journal of Machine Learning Research 17 (148), 1-5, 2016 | 39 | 2016 |
| Nearly isometric embedding by relaxation J McQueen, M Meila, D Joncas Advances in Neural Information Processing Systems 29, 2016 | 37 | 2016 |
| Improved graph Laplacian via geometric self-consistency D Joncas, M Meila, J McQueen Advances in Neural Information Processing Systems 30, 2017 | 27 | 2017 |
| Experimental design in marketplaces P Bajari, B Burdick, GW Imbens, L Masoero, J McQueen, TS Richardson, ... Statistical Science 38 (3), 458-476, 2023 | 20 | 2023 |
| megaman: Manifold Learning with Millions of points J McQueen, M Meila, J VanderPlas, Z Zhang arXiv preprint arXiv:1603.02763, 2016 | 11 | 2016 |
| A bayesian model for online activity sample sizes TS Richardson, Y Liu, J McQueen, D Hains International Conference on Artificial Intelligence and Statistics, 1775-1785, 2022 | 9 | 2022 |
| Evaluation of appropriate venous thromboembolism prophylaxis in patients with orthopaedic trauma with symptom-driven vascular and radiographic studies CM Domes, AM Schleyer, JM McQueen, RF Pergamit, DM Beingessner Journal of Orthopaedic Trauma 31 (12), 611-616, 2017 | 8 | 2017 |
| Modern manifold learning methods for md data–a step by step procedural overview YC Chen, J McQueen, SJ Koelle, M Meila, S Chmiela, A Tkatchenko | 6 | 2019 |
| Empirical Bayes for large-scale randomized experiments: a spectral approach FR Guo, J McQueen, TS Richardson arXiv preprint arXiv:2002.02564, 2020 | 5 | 2020 |
| Experimentation platforms meet reinforcement learning: Bayesian sequential decision-making for continuous monitoring R Wan, Y Liu, J McQueen, D Hains, R Song Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
| Improved graph laplacian via geometric consistency DC Perrault-Joncas, M Meila, J McQueen Proceedings of the 31st international conference on neural information …, 2017 | 4 | 2017 |
| Multiple Randomization Designs: Estimation and Inference with Interference L Masoero, S Vijaykumar, T Richardson, J McQueen, I Rosen, B Burdick, ... arXiv preprint arXiv:2401.01264, 2024 | 3 | 2024 |
| Estimating the Value of Evidence-Based Decision Making A Abadie, A Agarwal, G Imbens, S Jia, J McQueen, S Stepaniants arXiv preprint arXiv:2306.13681, 2023 | 2 | 2023 |
| Leveraging covariate adjustments at scale in online A/B testing L Masoero, D Hains, J McQueen The KDD'23 Workshop on Causal Discovery, Prediction and Decision, 25-48, 2023 | 1 | 2023 |
| Efficient switchback experiments via multiple randomization designs L Masoero, G Imbens, T Richardson, J McQueen, S Vijaykumar, I Rosen | 1 | 2023 |
| Top challenges from the first practical online controlled experiments summit B Smith, J McQueen | 1 | 2019 |
| Effect size estimation for duration recommendation in online experiments: Leveraging hierarchical models and objective utility approaches Y Liu, R Wan, J McQueen, D Hains, J Gu, R Song Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 14044 …, 2024 | | 2024 |
| Online testing efficiency through early termination Y Liu, R Wan, J McQueen, D Hains, R Song, RH Castillo US Patent 11,909,829, 2024 | | 2024 |
Marina MeilaUniversity of WashingtonVerified email at stat.washington.edu
