This lecture is the finale in the series about Karger's algorithm. Karger's is a Monte Carlo randomized algorithm to find the min cut in a graph that is almost correct in efficient time. In this last lecture we introduce an extension of Karger's algorithm, called Karger-Stein that makes smart moves regarding the repetition of the base algorithm, that is, repeat when necessary, to avoid starting over. We give formal proofs of the efficiency of the algorithm (an exponential speedup over the original Karger's) as well as an analysis of its probability of success. The instruction language is Arabic, however, all material, slides, definitions, concepts, examples, illustrations, etc., are all given in English.
