PPT-Welcome CSE4111/5111 Computability and Complexity

Jeff Edmonds York University Lecture 0 COSC 4111 Jeff Edmonds wwwcseyorkucajeff jeffcseyorkuca CSB 3044 ext 33295 4165387413  Course Material wwwcseyorkucajeffcourses4111. C Berkeley CS172 Automata Computability and Complexity Handout 1 Professor Luca Trevisan 232015 Notes on State Minimization These notes present a technique to prove a lower bound on the number of states of any D 045J18400J utomata Computability and Complexity Prof Nanc ynch Recitation 4 Distinguishable strings and indices ebruary 29 2007 Elena Grigor escu Pr oblem Quiz Questions Pr oblem Recall quiz question Ar gue t C Berkeley CS172 Automata Computability and Complexity Solutions to Problem Set 4 Professor Luca Trevisan 2232007 Solutions to Problem Set 4 1 Sipser Problem 313 A Turing machine with stay put instead of le )$ .2)!' ,$(), -. ,-5111-!( .),"5\f\f\r\r\t )$ .2)!' ,$(), -. ,-5111-!( .),"5\f\f\r\r\t ), -.,2' ," -.# -$ ( )!'("$("(.# )(- ,0.$)()!!), -., -)/, -7& (1. How to celebrate it, leverage it, and NOT avoid it!. Are YOU sufficiently complex?. Simple = Best. FROM OCCAM’S . RAZOR. COMPLEXITY. Are YOU sufficiently complex?. Simple = Best. Simple but no. Simpler. J Paul Gibson. TSP: . Mathematical. . Foundations. MAT7003/. L7-. Computability. .. 1. MAT 7003 : Mathematical Foundations. (for Software Engineering). J . Paul. Gibson, A207. paul.gibson@it-sudparis.eu. Lecture 1: . Intro; Turing machines; . Class P and NP . . . Indian Institute of Science. About the course. Computational complexity attempts . to classify computational . problems. How Understanding Complexity Promotes Simplicity. Why is writing software hard?. ^. great. http://www.infoq.com/presentations/Simple-Made-Easy. Our duty as software architects is to understand and manage complexity. 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. 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?. In this topic, we will:. Ask what is computable. Describe a Turing machine. Define Turing completeness. Computability. How do we define what is and what is not computable?. Is it possible to write a C++ function which cannot be written using Pascal, Java, or C#, or vice versa?. Pre - s Statewide H eal t hcare Emergency Codes ( Panic button can be used in conjunction with these codes , i f permitted by facility policy) Originally published January 2005, revised June 2016 CO 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.