PPT-1 Information complexity and exact communication bounds

April 26 2013 Mark Braverman Princeton University Based on joint work with Ankit Garg Denis Pankratov and Omri Weinstein Overview information complexity Information complexity . Shubhangi. . Saraf. Rutgers University. Based on joint works with . Albert Ai, . Zeev. . Dvir. , . Avi. . Wigderson. Sylvester-. Gallai. Theorem (1893). v. v. v. v. Suppose that every line through . China Theory Week, Aarhus. August 13, 2012. Today’s Goal:. To present new developments in a line of research dating back to 2002, presenting some unexpected connections between. Kolmogorov. Complexity (the theory of randomness), and. Progress and Obstacles. Rotem Oshman. ADGA 2013. Overview: Network Models. CONGESTED CLIQUE. ASYNC MESSAGE-PASSING. LOCAL. CONGEST / general network. X. Talk Overview. Lower bound techniques. CONGEST general networks: reductions from 2-party communication complexity. (as told by Michael Lynch). Genome size and complexity varies across the tree of life. Lynch 2007. Some Big Questions. What is the relationship between genomic and organismal size/complexity?. Are genome size changes adaptive, or passively acquired?. Shubhangi. . Saraf. Rutgers University. Based on joint works with . Albert Ai, . Zeev. . Dvir. , . Avi. . Wigderson. Sylvester-. Gallai. Theorem (1893). v. v. v. v. Suppose that every line through . A combinatorial approach to P . vs. NP. Shachar. Lovett. Computation. Input. Memory. Program . Code. Program code is . constant. Input has . variable length (n). Run time, memory – grow with input length. Rahul Jain. Centre for Quantum Technologies and. Department of Computer Science. National University of Singapore.. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . relaxations. via statistical query complexity. Based on:. V. F.. , Will Perkins, Santosh . Vempala. . . On the Complexity of Random Satisfiability Problems with Planted . Solutions.. STOC 2015. V. F.. June 1, 2013. Mark Braverman. Princeton University. a tutorial. Part I: Information theory. Information theory, in its modern format was introduced in the 1940s to study the problem of transmitting data over physical channels. . Fall . 2011. Sukumar Ghosh. What is an algorithm. . A finite set (or sequence) of . precise instructions . for performing a computation. . . . Example: Maxima finding. . . procedure . max. (. District Learning Day. Location goes here. Session time goes here. Date goes here. Do Now. Underline. the major points. . Use a question mark . (. ?. ) for keywords or phrases that are confusing or unknown to you or questions that you have during the reading. Be sure to write your question(s). . Second Biennial Seminar on the Philosophical Epistemological and Methodological Implications of Complexity Theory Havana Cuba January 2004ABSTRACT The sciences of complexity have recently revealed a dynamic data structures. Shachar. Lovett. IAS. Ely . Porat. Bar-. Ilan. University. Synergies in lower bounds, June 2011. Information theoretic lower bounds. Information theory. is a powerful tool to prove lower bounds, e.g. in data structures. Alexander A. . Razborov. University of . Chicago. Steklov. . Mathematical Institute . IAS, . Avi. is 60 conference, October 5, 2016. Subtitle: on my . (and others’) largely unsuccessful . attempts to make .