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Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire

License: GNU General Public License v3.0

Java 100.00%

java bandit-algorithm bandit-learning contextual-bandits linucb

linucb's Introduction

LinUCB

Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire.

We implemented the two version, one with disjoint and and one with hybrid linear models, as mentioned in the paper.

See src/de/thunfischtoast/BanditTest.java for basic usage example as inspired by http://john-maxwell.com/post/2017-03-17/ .

Reference:

@inproceedings{li2010contextual,
  title={A contextual-bandit approach to personalized news article recommendation},
  author={Li, Lihong and Chu, Wei and Langford, John and Schapire, Robert E},
  booktitle={Proceedings of the 19th international conference on World wide web},
  pages={661--670},
  year={2010},
  organization={ACM}
}

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yipeng5 yuan776 andy-wagner lfsblack zhouyu7373 zdd199212 youn-j laoma023012 agilemantis srinivas5599

linucb's Issues

What is HybridLinUCB and the none-shared-feature?

Hi ,
It is one greate java implement Linucb algorithm.
I am puzzled with HybridLinUCB's none-shared-feature.What is it?

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