Communication Complexity (for Algorithm Designers): 32 (Foundations and Trends in Theoretical Computer Science)
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Description
Communication Complexity (For Algorithm Designers) Collects The Lecture Notes From The AuthorS Eponymous Course Taught At Stanford In The Winter Quarter Of 2015. The Two Primary Goals Of The Text Are: (1) Learn Several Canonical Problems In Communication Complexity That Are Useful For Proving Lower Bounds For Algorithms (Disjointness, Index, GapHamming, And So On). (2) Learn How To Reduce Lower Bounds For Fundamental Algorithmic Problems To Communication Complexity Lower Bounds.Along The Way, Readers Will Also Get Exposure To A Lot Of Cool Computational Models And Some Famous Results About Them Data Streams And Linear Sketches, Compressive Sensing, SpaceQuery Time TradeOffs In Data Structures, SublinearTime Algorithms, And The Extension Complexity Of Linear Programs. Readers Are Assumed To Be Familiar With UndergraduateLevel Algorithms, As Well As The Statements Of Standard Large Deviation Inequalities (Markov, Chebyshev, And Chernoff Hoeffding).
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