| Hyperband: A novel bandit-based approach to hyperparameter optimization L Li, K Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar The Journal of Machine Learning Research 18 (1), 6765-6816, 2017 | 1900* | 2017 |
| Non-stochastic best arm identification and hyperparameter optimization K Jamieson, A Talwalkar Artificial intelligence and statistics, 240-248, 2016 | 409 | 2016 |
| lil’ucb: An optimal exploration algorithm for multi-armed bandits K Jamieson, M Malloy, R Nowak, S Bubeck Conference on Learning Theory, 423-439, 2014 | 333 | 2014 |
| A system for massively parallel hyperparameter tuning L Li, K Jamieson, A Rostamizadeh, E Gonina, J Ben-Tzur, M Hardt, ... Proceedings of Machine Learning and Systems 2, 230-246, 2020 | 240* | 2020 |
| Active ranking using pairwise comparisons KG Jamieson, R Nowak Advances in neural information processing systems 24, 2011 | 235 | 2011 |
| Best-arm identification algorithms for multi-armed bandits in the fixed confidence setting K Jamieson, R Nowak 2014 48th Annual Conference on Information Sciences and Systems (CISS), 1-6, 2014 | 141 | 2014 |
| Query complexity of derivative-free optimization KG Jamieson, B Recht, R Nowak Advances in Neural Information Processing Systems, 2672-2680, 2012 | 138 | 2012 |
| Hyperband: Bandit-based configuration evaluation for hyperparameter optimization L Li, KG Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar ICLR (Poster), 2017 | 108 | 2017 |
| Non-asymptotic gap-dependent regret bounds for tabular mdps M Simchowitz, KG Jamieson Advances in Neural Information Processing Systems 32, 2019 | 99 | 2019 |
| Low-dimensional embedding using adaptively selected ordinal data KG Jamieson, RD Nowak 2011 49th Annual Allerton Conference on Communication, Control, and …, 2011 | 73 | 2011 |
| Sequential experimental design for transductive linear bandits T Fiez, L Jain, KG Jamieson, L Ratliff Advances in neural information processing systems 32, 2019 | 68 | 2019 |
| Top arm identification in multi-armed bandits with batch arm pulls KS Jun, K Jamieson, R Nowak, X Zhu Artificial Intelligence and Statistics, 139-148, 2016 | 62 | 2016 |
| Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations M Laskey, C Chuck, J Lee, J Mahler, S Krishnan, K Jamieson, A Dragan, ... 2017 IEEE International Conference on Robotics and Automation (ICRA), 358-365, 2017 | 61 | 2017 |
| Next: A system for real-world development, evaluation, and application of active learning KG Jamieson, L Jain, C Fernandez, NJ Glattard, R Nowak Advances in neural information processing systems 28, 2015 | 58 | 2015 |
| Finite sample prediction and recovery bounds for ordinal embedding L Jain, KG Jamieson, R Nowak Advances in neural information processing systems 29, 2016 | 57 | 2016 |
| Sparse dueling bandits K Jamieson, S Katariya, A Deshpande, R Nowak Artificial Intelligence and Statistics, 416-424, 2015 | 56 | 2015 |
| The simulator: Understanding adaptive sampling in the moderate-confidence regime M Simchowitz, K Jamieson, B Recht Conference on Learning Theory, 1794-1834, 2017 | 49 | 2017 |
| A framework for multi-a (rmed)/b (andit) testing with online fdr control F Yang, A Ramdas, KG Jamieson, MJ Wainwright Advances in Neural Information Processing Systems 30, 2017 | 49 | 2017 |
| On finding the largest mean among many K Jamieson, M Malloy, R Nowak, S Bubeck arXiv preprint arXiv:1306.3917, 2013 | 33 | 2013 |
| An empirical process approach to the union bound: Practical algorithms for combinatorial and linear bandits J Katz-Samuels, L Jain, KG Jamieson Advances in Neural Information Processing Systems 33, 10371-10382, 2020 | 32 | 2020 |
Robert D NowakNosbusch Professor in Engineering and Wisconsin Institute for Discovery, UW-MadisonVerified email at wisc.edu
