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MIT开放课件 6.856J / 18.416J Randomized Algorithms Fall 2002

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Content within individual courses is (c) by the individual authors unless otherwise noted. Image is taken from NASA's Web site: http://www.nasa.gov. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions.</lom:string></lom:description></lom:rights><!--***************************--><!--**** RELATION ****--><!--***************************--><lom:relation><lom:kind uniqueElementName="kind"><lom:source uniqueElementName="source">LOMv1.0</lom:source><lom:value uniqueElementName="value">ispartof</lom:value></lom:kind><lom:resource uniqueElementName="resource"><lom:identifier><lom:catalog uniqueElementName="catalog">OCW Master Course Number</lom:catalog><lom:entry uniqueElementName="entry">6.856J Randomized Algorithms Fall 2002</lom:entry></lom:identifier><lom:description><lom:string language="en">Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms. 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