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Lecture Algorithm design - Chapter 12: Local search include all of the content: Gradient descent, metropolis algorithm, hopfield neural networks, maximum cut, nash equilibria. Inviting you refer. | 12. Local Search gradient descent Metropolis algorithm Hop field neural networks maximum cut Nash equilibria Lecture slides by Kevin Wayne Copyright 2005 Pearson-Addison Wesley Copyright 2013 Kevin Wayne http www.cs.princeton.edu wayne kleinberg-tardos Last updated on Sep 8 2013 6 54 AM Coping With NP-hardness Q. Suppose I need to solve an NP-hard problem. What should I do A. Theory says you re unlikely to find poly-time algorithm. Must sacrifice one of three desired features. Solve problem to optimality. Solve problem in polynomial time. Solve arbitrary instances of the problem. 2 Section 12.1 12. Local Search gradient .
