PPT-Optimal bounds

on approximation of submodular and XOS functions by juntas Vitaly Feldman and Jan Vondrâk IBM Research Almaden Prelims Submodular and XOS Functions Learning 20 27. Our result is modular 1 We describe a carefullychosen dynamic version of set disjointness the multiphase problem and conjecture that it requires 84861 time per operation All our lower bounds follow by easy reduction 2 We reduce 3SUM to the multipha Indeed developing bounds on the per formance of procedures can give complementary insights By exhibiting fundamental limits of performance perhaps over restricted classes of estimators it is possible to guarantee that an a lgorithm we have developed Price of . Anarchy Bounds via Smoothness Arguments. Tim . Roughgarden. Stanford University. 2. Price of Anarchy. Definition:. . price of anarchy (POA) . of a game (. w.r.t. . some objective . function, . Robust Approximation Bounds for . Equilibria. and Auctions. Tim . Roughgarden. Stanford University. 2. Motivation. Clearly: . many modern applications in CS involve autonomous, self-interested agents. 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 . 2 - . Calculations. www.waldomaths.com. Copyright © . Waldomaths.com. 2010, all rights reserved. Two ropes, . A. and . B. , have lengths:. A = . 36m to the nearest metre . B = . 23m to the nearest metre.. 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 . Junier. . Oliva. 10-701. 2/19/2013. Useful Inequalities. Markov’s Inequality:. Chebyshev’s. Inequality:. Convergence in Distribution. Notation:. Definition:. . Convergence in . P. th. Mean, . unseen problems. David . Corne. , Alan Reynolds. My wonderful new algorithm, . Bee-inspired Orthogonal Local Linear Optimal . Covariance . K. inetics . Solver. Beats CMA-ES on 7 out of 10 test problems !!. approximate membership. dynamic data structures. Shachar. Lovett. IAS. Ely . Porat. Bar-. Ilan. University. Synergies in lower bounds, June 2011. Information theoretic lower bounds. Information theory. 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. A PRIORI BOUNDS ON THE PERFORMANCE OFOPTIMAL SYSTEMSbyROBERTO CANALES RUIZIE Universidad de los Andes1963BS Massachusetts Institute of Technology1963MS Massachusetts Institute of Technology1965SUBMITT 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. 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.