'Complete problems' presentation slideshows

NPC

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Chapter 10

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NEST Final Experiment: the application layer

NEST Final Experiment: the application layer. Phoebus Chen, Songhwai Oh, Bruno Sinopoli EECS UC Berkeley September 8, 2005. Outline. The application: Multiple-target tracking problem Pursuit Evasion Game The implementation The nitty gritty The result: Demonstration.

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NP -Completeness

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NP -Completeness

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Joint work with :

An Introduction to Parallel Computation and ? -Completeness Theory by Raymond Greenlaw. Joint work with :. Larry Ruzzo Department of Computer Science University of Washington. Jim Hoover Computing Science Department University of Alberta. Outline. Introduction Parallel Models of Computation

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Fragment Assembly of DNA

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DNA Computing by Self Assembly

Erik Winfree, Caltech. DNA Computing by Self Assembly. Self Assembly of a Box. Information and Algorithms. Electronic microprocessors control electro-mechanical devices Biochemical circuits control molecular/chemical events

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Toward NP-Completeness: Introduction

Toward NP-Completeness: Introduction. Almost all the algorithms we studies so far were bounded by some polynomial in the size of the input, so we call them efficient algorithms.

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Absolute Value Equation Solution via Concave Minimization

Absolute Value Equation Solution via Concave Minimization. Olvi Mangasarian University of Wisconsin - Madison University of California at San Diego. What is the Absolute Value Equation (AVE)?. Simplest Solvable AVE in 1-Dimension. Why the Absolute Value Equation ?. Because the AVE subsumes:

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NP-completeness

Giorgi Japaridze Theory of Computability. NP-completeness. Section 7.4. 7.4.a. Giorgi Japaridze Theory of Computability. Importance. NP-complete problems form a certain important subclass of NP . The phenomenon of NP-completeness was discovered in the early 1970s

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Capabilities and limitations of quantum computers

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Lecture 19 P-Complete Problems

Lecture 19 P-Complete Problems. Log-space many-one reduction. DEFINITION. PROPERTY. P-complete. Circuit Value Problem (CVP). THEOREM. PROOF. SIMULATE DTM COMPUTATION BY A CIRCUIT. Planar Circuit Value (PCV). THEOREM. PROOF. Monotone Circuit Value (MCV). THEOREM. PROOF.

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CSE 421 Algorithms

CSE 421 Algorithms. Richard Anderson Lecture 29 NP-Completeness. Sample Problems. Independent Set Graph G = (V, E), a subset S of the vertices is independent if there are no edges between vertices in S. 1. 2. 3. 5. 4. 6. 7. Satisfiability.

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Unit 5

Unit 5. Section 5.4 Functions and Relations. Function. To determine if a graph is a function, we perform the vertical line test . . PASS. -- Yes, it is a function. FAIL. -- No, it is not a function. Function. Vertical Line Test: 1.Draw a vertical line through the graph.

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Introduction to NP-Completeness

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CS 332: Algorithms

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4-6 6 th grade math

4-6 6 th grade math. Least Common Multiple LCM. Objective. To find the least common multiple (LCM) of two or three numbers. Why? To help you find the common denominator when simplifying fractions. To help you find a commonality between numbers. California State Standards .

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Warm- up

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