The K-armed Dueling Bandits Problem

@article{Yue2009TheKD,
  title={The K-armed Dueling Bandits Problem},
  author={Yisong Yue and Josef Broder and Robert D. Kleinberg and Thorsten Joachims},
  journal={J. Comput. Syst. Sci.},
  year={2009},
  volume={78},
  pages={1538-1556}
}
We study a partial-information online-learning problem where actions are restricted to noisy comparisons between pairs of strategies (also known as bandits). In contrast to conventional approaches that require the absolute reward of the chosen strategy to be quantifiable and observable, our setting assumes only that (noisy) binary feedback about the relative reward of two chosen strategies is available. This type of relative feedback is particularly appropriate in applications where absolute… CONTINUE READING
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Showing 1-10 of 17 references

How do we get weak action dependence for learning with partial observations? http://hunch.net/?p=421

John Langford
2008

, and Thorsten Joachims . How does clickthrough data reflect retrieval quality ?

Madhu Kurup
SIAM Conference on Data Mining ( SDM ) • 2007

Regret Minimization Under Partial Monitoring

2006 IEEE Information Theory Workshop - ITW '06 Punta del Este • 2006

Tsitsiklis , The sample complexity of exploration in the multi - armed bandit problem

Shie Mannor, N. John
J . Mach . Learn . Res . • 2004

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