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From External To Internal Regret (Section 7).pdf

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Preview of From External to internal regret (Section 7)
🔗 Source: jmlr.org
📊 Size: 159 KB
📄 Pages: 18 pages
⬇️ Downloads: 123

Summary

Journal of Machine Learning Research 8 (2007) 1307-1324:
Avrim Blum and Yishay Mansour present a simple generic reduction to convert an algorithm for the external regret problem into an efficient online algorithm for the internal regret problem, in both full information and partial information (bandit) models.
They derive a quantitative regret bound for a general setting of regret and show that internal regret is connected to correlated equilibria.
The authors provide a swap regret bound of O(√TN logN) and an Ω(√TN) lower bound for randomized online algorithms against an adaptive adversary.
They also extend their results to the partial information model, achieving an O(N√NT logN) swap-regret bound for the multi-armed bandit setting.

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Journal of Machine Learning Research 8 (2007) 1307-1324:
Avrim Blum and Yishay Mansour present a simple generic reduction to convert an algorithm for the...

Technical Information

  • File Format: PDF
  • File Size: 159 KB
  • Pages: 18
  • Language: EN
  • Total Downloads: 123
  • Last Updated: 4 days ago

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