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Lecture 4 | September 11 4.1 Gradient Descent

Lecture 4 | September 11 4.1 Gradient Descent

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EE 381V Lecture 4 | September 11 Fall 2012 4.1.1 Strong Convexity and implications De nition: If there exist a constant m>0 such that r2f mIfor all x2S, then the function f(x) is a strongly convex function on S.

  Lecture, September, Descent, Derating, Lecture 4 september 11 4, 1 gradient descent, Lecture 4 september 11

6.1 Gradient Descent: Convergence Analysis

6.1 Gradient Descent: Convergence Analysis

www.stat.cmu.edu

Lecture 6: September 12 6-3 6.1.2 Convergence of gradient descent with adaptive step size We will not prove the analogous result for gradient descent with backtracking to adaptively select the step size. Instead, we just present the result with a few comments.

  Lecture, September, Descent, Derating, 1 gradient descent, Gradient descent

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