NeurIPS 2020poster43 citations
Efficient Contextual Bandits with Continuous Actions
Maryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins
Abstract
We create a computationally tractable learning algorithm for contextual bandits with continuous actions having unknown structure. The new reduction-style algorithm composes with most supervised learning representations. We prove that this algorithm works in a general sense and verify the new functionality with large-scale experiments.
BibTeX
@inproceedings{NEURIPS2020_033cc385,
author = {Majzoubi, Maryam and Zhang, Chicheng and Chari, Rajan and Krishnamurthy, Akshay and Langford, John and Slivkins, Aleksandrs},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {349--360},
publisher = {Curran Associates, Inc.},
title = {Efficient Contextual Bandits with Continuous Actions},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/033cc385728c51d97360020ed57776f0-Paper.pdf},
volume = {33},
year = {2020}
}