PPT-Parameterized Complexity

Part I Basics Kernels and Branching Daniel Lokshtanov Basics Motivation If L is NPhard then there is no algorithm which solves all instances of L in polynomial time What about the . Ian Bertolacci – Colorado State University. Catherine . Olschanowsky. – Colorado State University. Ben . Harshbarger. – Cray Inc.. Bradford L. . Chamerlain. – Cray Inc.. David G. . Wonnacott. Closest String with Wildcards. (CSW). Problem. Danny . Hermelin. Liat. . Rozenberg. CPM - Moscow - June 2014. The Closest String problem. Given. :. a set of . m. strings, each of length . Principles, Techniques, and Applications in Practice. Tutorial. Nikolai Tillmann, Peli de Halleux, Wolfram Schulte. (Microsoft Research). Tao . Xie. (North Carolina State University). Outline. Unit Testing. Tao Xie . North Carolina. State University. Nikolai Tillmann, . Peli de Halleux, . Wolfram Schulte. . Microsoft Research. Outline. Unit Testing. Parameterized Unit Testing (PUT). Mutation Analysis for PUT. Lecture 1: . Intro; Turing machines; . Class P and NP . . . Indian Institute of Science. About the course. Computational complexity attempts . to classify computational . problems. The Basics. Bart . M. P. . Jansen. Insert. «. Academic. unit» . on every page:. 1 Go to the menu «Insert». 2 Choose: Date and time. 3 Write the name of your faculty or department in the field «Footer». Theophilus Benson (tbenson@cs.wisc.edu). Aditya Akella (akella@cs.wisc.edu). David A Maltz (dmaltz@microsoft.com). Enterprise Networks. Intricate logical and physical topologies. Diverse network devices. Parameterization. Parameterization is used to change the value of any variable at run time.. Following can be parameterized in a script file:-.  . URL portion.  . Header portion.  . BODY portion. Wing Lam (U. Illinois). In collaboration with . Siwakorn. . Srisakaokul. , Blake Bassett, . Peyman. . Mahdian. and Tao . Xie. (U. Illinois). Nikolai Tillman, Jonathan de . Halleux. . (Microsoft Research) . using Parameterized Program Equivalence. University of California, San Diego. Sudipta. . Kundu. Zachary . Tatlock. Sorin. Lerner. Compiler Correctness. Difficult to develop reliable compilers:. large, complex programs. 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. What is the best way to measure the time complexity of an algorithm?. - Best-case run time?. - Worst-case run time?. - Average run time?. Which should we try to optimize?. Best-Case Measures. How can we modify almost any algorithm to have a good best-case running time?. PI: Cristiana Stan, George Mason University/COLA. Atlantic wind-shear and its relationship with ENSO. S. ummer precipitation in the . eastern . U.S. . . Acknowledgement: . Xiaojie. Zhu and Li . Xu. 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.