PPT-Exponentially improved algorithms and lower bounds

for testing signed majorities Dana Ron Tel Aviv University Rocco A Servedio Columbia University Testing properties of Boolean functions the basics Let C be a class of Boolean functions mapping . 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 for Linear Algebra and Beyond. Jim . Demmel. EECS & Math Departments. UC Berkeley. 2. Why avoid communication? (1/3). Algorithms have two costs (measured in time or energy):. Arithmetic (FLOPS). Communication: moving data between . comparison model in which the only operations allowed that involve x are com- parisons between x and elements of S. Using binary search, predecessor and membership queries can be performed in O(logn) Razvan. . Carbunescu. 12/02/2011. 1. Outline (1/2). Sequential general LU factorization (GETRF) and Lower Bounds. Definitions and Lower Bounds. LAPACK algorithm. Communication cost. Summary. Sequential banded LU factorization (GBTRF) and Lower Bounds. Reticulate Network of Multiple . Phylogenetic. Trees. Yufeng. . Wu. Dept. of Computer Science & Engineering. University of Connecticut, USA. ISMB 2010. 1. 1. 2. 3. 4. Keep. two . red. edges. Keep. 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 . exponential decay. .. The constant k has units of “inverse time”; . if t . is measured in days, then k has units of. (days). −1. .. In the laboratory, the number of . Escherichia coli. bacteria . Lower Bounds, and Pseudorandomness. Igor Carboni Oliveira. University of Oxford. Joint work with . Rahul Santhanam. (Oxford). 2. Minor algorithmic improvements imply lower bounds (Williams, 2010).. NEXP. Knowledge Compilation: Representations and Lower Bounds Paul Beame University of Washington with Jerry Li, Vincent Liew , Sudeepa Roy, Dan Suciu Representing Boolean Functions Circuits Boolean formulas (tree-like circuits), CNFs, DNFs 10 Bat Algorithms Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 The bat algorithm (BA) is a bio-inspired algorithm developed by Xin-She Yang in 2010. 10.1 Echolocation of Bats New and Improved VA Algorithms / New SPHM App! Marie Martin, PhD Kurk A. Rogers, RN, BSN, CNOR, MBA (CDR, NC, USN [ RET ]) With information from Mary W. Matz, MSPH, CPE, CSPHP Objectives On completion of this training program, participants will be able to: 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. . Efficient algorithms = run time, memory . 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. 0. Joint work with . Ruiwen Chen. and . Rahul Santhanam. Igor C. Oliveira. University of Oxford. 1. Context and Background. 2. Establish . unconditional. . lower bounds on . the complexity of computations..