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Optimal Brain Surgeon Algorithm

Optimal Brain Surgeon Algorithm. Randy Skala ECE 539 Section 1. Summary of Algorithm. Train the multilayer perceptron to a minimum in mean square error Compute the inverse Hessian (H -1 ) Eliminate weights will small saliencies

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Optimal Brain Surgeon Algorithm

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  1. Optimal Brain Surgeon Algorithm Randy Skala ECE 539 Section 1

  2. Summary of Algorithm • Train the multilayer perceptron to a minimum in mean square error • Compute the inverse Hessian (H-1) • Eliminate weights will small saliencies • Repeat until no more weights can be deleted without a large increase in the mean-square error.

  3. Computational Hurdles of the OBS algorithm • Computing the inverse Hessian matrix • Recursive formula has order greater than n2 • Many Recursions are needed for convergence • Updating the Weights, Hessian matrix and Saliencies every time a weight is eliminated • Many weights are typically eliminated

  4. Simplifying the OBS • Estimate dF/dw by finding the change in the cost function when each weight is eliminated • Use the initial Hessian matrix for all updates • Do “batch elimination” of weights

  5. Results • Incomplete • Results so far seem to show that classification problems are handled well with the simplification. • Estimation problems do not seem to work as well.

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