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CLOP for Noisy Black-Box Parameter Optimization,
a program used for parameter tuning, created by Rémi Coulom. The CLOP principle, which stands for Confident Local OPtimization [1], is an approach to local regression that overcomes problems with very noisy outputs and nonnegative Hessians [2] in a simple and efficient way. CLOP is suited to tune several parameters simultaneously, and requires polynomial time for each additional parameter to verify the tuned values, that is playing a lot of games [3].

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External Links


References

  1. ^ CLOP: Confident Local Optimization for Noisy Black-Box Parameter Tuning
  2. ^ Second partial derivative test from Wikipedia
  3. ^ Re: How Do You Automatically Tune Your Evaluation Tables by Jon Dart, CCC, January 31, 2014
  4. ^ The Inventions - Les Paul

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