Faster gradient descent and the efficient recovery of images

12 Aug 2013Hui HuangUri Ascher

Much recent attention has been devoted to gradient descent algorithms where the steepest descent step size is replaced by a similar one from a previous iteration or gets updated only once every second step, thus forming a {\em faster gradient descent method}. For unconstrained convex quadratic optimization these methods can converge much faster than steepest descent... (read more)

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