'Np complete problems' diaporamas de présentation

Public key ciphers 1

Public key ciphers 1. Session 5. Contents. Intractability and NP- completness Primality testing Factoring large composite numbers Complexity of RSA Security of RSA. Intractability and NP- completness. A problem A general question that must be answered

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Optical Solutions for Bounded NP-Complete Problems

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From Decision to Optimization and Enumeration

From Decision to Optimization and Enumeration. 7.3.1 to 7.3.3. 7.3.1. Turing Reductions and Search problems. In the Beginning. When studying complexity theory we generally restrict our problems to decision problems. This is done to ease the study.

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On the Compressibility of NP instances and Cryptographic Applications,

On the Compressibility of NP instances and Cryptographic Applications,. Danny Harnik. Moni Naor. Weizmann Institute of Science. Technion. Key Idea of Cryptography. Use the intractability of some problems for the advantage of constructing secure systems.

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NP-Completeness

NP-Completeness. Objectives : At the end of the lesson, students should be able to: 1. Differentiate between class P, NP, and NPC 2. Reduce a known NPC problem into another NPC problem 3. Show a given problem is in NPC 4. Solve a problem using an approximate solution. Content.

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Computational Intractability As A Law of Physics

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Algorithms and Running Time

Algorithms and Running Time Algorithm: Well defined and finite sequence of steps to solve a well defined problem. Eg.,, Sequence of steps to multiply two numbers. Algorithms are meant to solve all instances of problems for which they are designed.

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How Much Information Is In A Quantum State?

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Complexity Classes: P and NP

Complexity Classes: P and NP. CS 130 Theory of Computation HMU Textbook: Chap 10. Turing machines and complexity. Time and space complexity The class P Non-determinism The class NP Reduction and NP-Completeness. Time and space complexity.

1.61k views • 26 slides

What is Computing? Informatics?

What is Computing? Informatics?. What is computer science, what is its potential? What can we do with computers in our lives? What can we do with computing for society? Will networks transform thinking/knowing/doing? Society affecting and affected by computing?

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Sep 16, 2013

Computational social choice The easy-to-compute axiom. Lirong Xia. Sep 16, 2013. Topics for paper presentation is available online. On average one student one paper group of two: two times group of three: three times You need to prepare the slides

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Optimization Problems

Optimization Problems. Greg Stitt ECE Department University of Florida. Introduction. Why are we studying optimization problems? Just about every RC-tool related issue is an optimization problem This lecture should provide abstract solutions to many RC tool problems. Time Complexity.

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ASP vs. Prolog like programming

ASP vs. Prolog like programming. ASP is adequate for: NP-complete problems situation where the whole program is relevant for the problem at hands If the problem is polynomial, why using such a complex system?

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The Traveling Salesman Problem

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CSCI920 (Week 13)

CSCI920 (Week 13). Revision (II) Guilin Wang SCSSE Nov. 2010. Contact Info. Email: guilin@uow.edu.au Room: 3.203 Consultation times (updated): - Mon.: 14-16pm - Wed.: 11-13pm URL: http://www.uow.edu.au/~guilin/. Outline. Revision Strategies Exam Tips

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Complexity Classes

Complexity Classes. Chapter 8 (Abbreviated). Overview. Problems are classified according to the resources they use on computing machines (serial or parallel) Serial models are RAM and Turing machines Parallel models are the circuit and PRAM Terms of discussion are first defined

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Design and Analysis of Algorithms NP-Completeness

Design and Analysis of Algorithms NP-Completeness. Haidong Xue Fall 2013, at GSU. What is polynomial-time?. Polynomial-time: running time is , where k is a constant. Are they polynomial-time running time? yes yes yes yes. What is polynomial-time?. Are the polynomial-time? No No

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Limits to Computation

Limits to Computation. How do you analyze a new algorithm? Put it in the form of existing algorithms that you know the analysis. For example, given 2 arrays, pair the smallest in each array, the next smallest, etc. Can be done by sorting each array and pairing first, second, etc.

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