Algorithms for Hyper-Parameter Optimization

NeurIPS 2011 James S. BergstraRémi BardenetYoshua BengioBalázs Kégl

Several recent advances to the state of the art in image classification benchmarks have come from better configurations of existing techniques rather than novel approaches to feature learning. Traditionally, hyper-parameter optimization has been the job of humans because they can be very efficient in regimes where only a few trials are possible... (read more)

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