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 . cmuedu Joshua Brody IIIS ITCS Tsinghua University Beijing China joshuaebrodygmailcom Kevin Matulef IIIS ITCS Tsinghua University Beijing China matulefgmailcom Abstract We develop a new technique for proving lower bounds in property testing by showing 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. :. . The Basics, Accomplishments, Connections and Open problems. Toniann. . Pitassi. University of Toronto. Overview. P. roof systems we will cover. Propositional, Algebraic, Semi-Algebraic. Lower bound methods. 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.. 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.: . Andris Ambainis (Latvia), . Martins Kokainis (Latvia), . Robin Kothari (MIT). communication complexity. Alice holds . x. X. , Bob holds . y. Y. .. D. cc. (f). - minimum amount of communication to compute . Paul . Beame. University of Washington. Outline. Branching program basics. Space (size) lower bounds. Multi-output functions. Time-Space tradeoff lower bounds for general BPs. Single-output functions. David P. Woodruff. IBM . Almaden. Talk Outline. Information Theory Concepts. Distances Between Distributions. An Example Communication Lower Bound – Randomized 1-way Communication Complexity of the INDEX problem. Toniann. . Pitassi. University of Toronto. 2-Party Communication Complexity. [Yao]. 2-party communication: . each party has a dataset. . Goal . is to compute a function f(D. A. ,D. B. ). m. 1. m. 2. 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. . Lijie. Chen. MIT. Today’s Topic. Background. . What is Fine-Grained Complexity?. The Methodology of Fine-Grained Complexity. Frontier: Fine-Grained Hardness for Approximation Problems. The Connection. 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 . Dagstuhl Workshop. March/. 2023. Igor Carboni Oliveira. University of Warwick. 1. Join work with . Jiatu. Li (Tsinghua). 2. Context. Goals of . Complexity Theory. include . separating complexity classes.