Kevin Jamieson
Kevin Jamieson
Associate Professor, University of Washington
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
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
Non-stochastic best arm identification and hyperparameter optimization
K Jamieson, A Talwalkar
Artificial intelligence and statistics, 240-248, 2016
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
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
Active ranking using pairwise comparisons
KG Jamieson, R Nowak
Advances in neural information processing systems 24, 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
Query complexity of derivative-free optimization
KG Jamieson, B Recht, R Nowak
Advances in Neural Information Processing Systems, 2672-2680, 2012
Hyperband: Bandit-based configuration evaluation for hyperparameter optimization.
L Li, KG Jamieson, G DeSalvo, A Rostamizadeh, A Talwalkar
ICLR (Poster), 53, 2017
Non-asymptotic gap-dependent regret bounds for tabular mdps
M Simchowitz, KG Jamieson
Advances in Neural Information Processing Systems 32, 2019
Sequential experimental design for transductive linear bandits
T Fiez, L Jain, KG Jamieson, L Ratliff
Advances in neural information processing systems 32, 2019
Low-dimensional embedding using adaptively selected ordinal data
KG Jamieson, RD Nowak
2011 49th Annual Allerton Conference on Communication, Control, and …, 2011
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
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
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
The simulator: Understanding adaptive sampling in the moderate-confidence regime
M Simchowitz, K Jamieson, B Recht
Conference on Learning Theory, 1794-1834, 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
Finite sample prediction and recovery bounds for ordinal embedding
L Jain, KG Jamieson, R Nowak
Advances in neural information processing systems 29, 2016
Sparse dueling bandits
K Jamieson, S Katariya, A Deshpande, R Nowak
Artificial Intelligence and Statistics, 416-424, 2015
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
Reward-free rl is no harder than reward-aware rl in linear markov decision processes
AJ Wagenmaker, Y Chen, M Simchowitz, S Du, K Jamieson
International Conference on Machine Learning, 22430-22456, 2022
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Artikkelit 1–20