PPT-Algorithms for hard problems

Parameterized complexity Bounded tree width approaches Juris Viksna 2015 Tree decomposition of graph The purpose of the 1 in the definition of the width of a decomposition is to let trees have tree width 1. Richard M. Karp. Bangalore, January 5, 2011. NP-Hard Problems. The P vs. NP problem: Is finding a solution to a combinatorial search problem as easy as checking a solution. The answer is expected to be “No.”. . NP-Complete. CSE 680. Prof. Roger Crawfis. Polynomial Time. Most (but not all) of the algorithms we have studied so far are easy, in that they can be solved in polynomial time, be it linear, quadratic, cubic, etc.. Rahul. . Santhanam. University of Edinburgh. Plan of the Talk. Preliminaries and Motivation. Informational Bottlenecks: Proof Complexity and Related Models. Computational Bottlenecks: OPP and Compression. Lessons Learned.. Benefits.. Overview MCTP project. Administrative support is crucial!. Secretarial support.. W9s, waivers, created . reqs. , reserving rooms, reviewing applications, details all over the place!. vs. Algebraic. Computational Problems. Boaz Barak – MSR New England. Based on joint works with Benny Applebaum, Guy Kindler, . David . Steurer, . and . Avi Wigderson . Erd. ő. s Centennial, Budapest, July 2013. Nattee Niparnan. Easy & Hard Problem. What is “difficulty” of problem?. Difficult. . for . computer scientist. to derive algorithm for the problem?. Difficult for . computer. to solve (run the derived algorithm) the problem?. Roshanak Zakizadeh. 1. . Michael Brown. 2. Graham Finlayson. 1. 1. University of East Anglia . 2. National University of Singapore. Color. & Photometry in Computer Vision Workshop ICCV2015. Santiago, Chile. (a brief introduction to theoretical computer science). slides by Vincent Conitzer. Set Cover . (a . computational problem. ). We are given:. A finite set S = {1, …, n}. A collection of subsets of S: S. Context. Final Year. 120 credits (1 credit . approx. 10 hours). 30 credit project. 4 modules in semester 1 . 4 modules in semester 2. A module is 10 credits. 1 c. ompulsory . module on Prof Issues. Students select 4 modules from 8 in each semester. Joint work with Marek . Cygan, Holger Dell, Daniel Lokshtanov, Daniel . Marx, Yoshio . Okamoto, Ramamohan Paturi, Saket Saurabh and Magnus Wahlstrom. CCC 2012. Jesper Nederlof (Utrecht University, The Netherlands). Lessons Learned.. Benefits.. Overview MCTP project. Administrative support is crucial!. Secretarial support.. W9s, waivers, created . reqs. , reserving rooms, reviewing applications, details all over the place!. Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem.. and Cluster Analysis. Dissertation Defense. Nan Li. Committee. : Dr. . Longin. Jan . Latecki. (Advisor). Dr. . Haibin. Ling. Dr. Slobodan . Vucetic. Richard M. Karp. Bangalore, January 5, 2011. NP-Hard Problems. The P vs. NP problem: Is finding a solution to a combinatorial search problem as easy as checking a solution. The answer is expected to be “No.”.