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 | 836* | 2017 |
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 | 263 | 2014 |
Active ranking using pairwise comparisons KG Jamieson, RD Nowak arXiv preprint arXiv:1109.3701, 2011 | 201 | 2011 |
Non-stochastic best arm identification and hyperparameter optimization K Jamieson, A Talwalkar Artificial Intelligence and Statistics, 240-248, 2016 | 199 | 2016 |
Query complexity of derivative-free optimization KG Jamieson, B Recht, R Nowak Advances in Neural Information Processing Systems, 2672-2680, 2012 | 119 | 2012 |
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 | 102 | 2014 |
Efficient hyperparameter optimization and infinitely many armed bandits L Li, KG Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar CoRR, abs/1603.06560 16, 2016 | 95 | 2016 |
Hyperband: Bandit-Based Configuration Evaluation for Hyperparameter Optimization. L Li, KG Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar ICLR (Poster), 2017 | 72 | 2017 |
Low-dimensional embedding using adaptively selected ordinal data KG Jamieson, RD Nowak 2011 49th Annual Allerton Conference on Communication, Control, and …, 2011 | 62 | 2011 |
Massively parallel hyperparameter tuning L Li, K Jamieson, A Rostamizadeh, E Gonina, M Hardt, B Recht, ... | 60 | 2018 |
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 | 48 | 2017 |
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning. KG Jamieson, L Jain, C Fernandez, NJ Glattard, RD Nowak NIPS, 2656-2664, 2015 | 47 | 2015 |
Non-asymptotic gap-dependent regret bounds for tabular MDPs M Simchowitz, K Jamieson arXiv preprint arXiv:1905.03814, 2019 | 46 | 2019 |
Finite sample prediction and recovery bounds for ordinal embedding L Jain, K Jamieson, R Nowak arXiv preprint arXiv:1606.07081, 2016 | 46 | 2016 |
Sparse dueling bandits K Jamieson, S Katariya, A Deshpande, R Nowak Artificial Intelligence and Statistics, 416-424, 2015 | 45 | 2015 |
The simulator: Understanding adaptive sampling in the moderate-confidence regime M Simchowitz, K Jamieson, B Recht Conference on Learning Theory, 1794-1834, 2017 | 38 | 2017 |
A framework for Multi-A (rmed)/B (andit) Testing with Online FDR Control F Yang, A Ramdas, K Jamieson, MJ Wainwright arXiv preprint arXiv:1706.05378, 2017 | 38 | 2017 |
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 | 38 | 2016 |
On finding the largest mean among many K Jamieson, M Malloy, R Nowak, S Bubeck arXiv preprint arXiv:1306.3917, 2013 | 23 | 2013 |
A system for massively parallel hyperparameter tuning L Li, K Jamieson, A Rostamizadeh, E Gonina, M Hardt, B Recht, ... arXiv preprint arXiv:1810.05934, 2018 | 18 | 2018 |