Articles with public access mandates - Kevin JamiesonLearn more
Available somewhere: 31
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
Mandates: US Department of Defense
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
Mandates: US National Science Foundation
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
Mandates: US Department of Defense
Finite sample prediction and recovery bounds for ordinal embedding
L Jain, KG Jamieson, R Nowak
Advances in neural information processing systems 29, 2016
Mandates: US National Science Foundation, US National Institutes of Health
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US National Science Foundation
Active learning for identification of linear dynamical systems
A Wagenmaker, K Jamieson
Conference on Learning Theory, 3487-3582, 2020
Mandates: US National Science Foundation
High-dimensional experimental design and kernel bandits
R Camilleri, K Jamieson, J Katz-Samuels
International Conference on Machine Learning, 1227-1237, 2021
Mandates: US National Science Foundation
The true sample complexity of identifying good arms
J Katz-Samuels, K Jamieson
International Conference on Artificial Intelligence and Statistics, 1781-1791, 2020
Mandates: US National Science Foundation
Beyond no regret: Instance-dependent pac reinforcement learning
AJ Wagenmaker, M Simchowitz, K Jamieson
Conference on Learning Theory, 358-418, 2022
Mandates: US National Science Foundation, US Department of Defense
First-order regret in reinforcement learning with linear function approximation: A robust estimation approach
AJ Wagenmaker, Y Chen, M Simchowitz, S Du, K Jamieson
International Conference on Machine Learning, 22384-22429, 2022
Mandates: US National Science Foundation, US Department of Defense
Improved corruption robust algorithms for episodic reinforcement learning
Y Chen, S Du, K Jamieson
International Conference on Machine Learning, 1561-1570, 2021
Mandates: US National Science Foundation
Instance-dependent near-optimal policy identification in linear mdps via online experiment design
A Wagenmaker, KG Jamieson
Advances in Neural Information Processing Systems 35, 5968-5981, 2022
Mandates: US National Science Foundation, US Department of Defense
The power of adaptivity in identifying statistical alternatives
KG Jamieson, D Haas, B Recht
Advances in Neural Information Processing Systems 29, 2016
Mandates: US National Science Foundation, US Department of Energy
Best-of-k-bandits
M Simchowitz, K Jamieson, B Recht
Conference on Learning Theory, 1440-1489, 2016
Mandates: US National Science Foundation
Best arm identification with safety constraints
Z Wang, AJ Wagenmaker, K Jamieson
International Conference on Artificial Intelligence and Statistics, 9114-9146, 2022
Mandates: US National Science Foundation
Improved algorithms for agnostic pool-based active classification
J Katz-Samuels, J Zhang, L Jain, K Jamieson
International Conference on Machine Learning, 5334-5344, 2021
Mandates: US National Science Foundation
Instance-optimal pac algorithms for contextual bandits
Z Li, L Ratliff, KG Jamieson, L Jain
Advances in Neural Information Processing Systems 35, 37590-37603, 2022
Mandates: US National Science Foundation
Active learning with safety constraints
R Camilleri, A Wagenmaker, JH Morgenstern, L Jain, KG Jamieson
Advances in Neural Information Processing Systems 35, 33201-33214, 2022
Mandates: US National Science Foundation, US Department of Defense
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