'Complexity class' presentation slideshows

Design and Analysis of Approximation Algorithms

Design and Analysis of Approximation Algorithms. Ding-Zhu Du. Text Books. Ding-Zhu Du and Ker-I Ko, Design and Analysis of Approximation Algorithms (Lecture Notes). Chapters 1-8. Schedule. Introduction Greedy Strategy Restriction Partition Guillotine Cut Relaxation

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Complexity and Cryptography

Complexity and Cryptography. Haya Shulman CGC Colloquium. Complexity Theory. Determines complexity (power and limitations) of well defined tasks Defines resources required to solve computational problems E.g. time, space, randomness, interaction

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NP Completeness and Approximation algorithms

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David Evans cs.virginia/evans

Class 22: Classy Complexity Classes. Office hours note: my office hours tomorrow will be 10-11am in my office. David Evans http://www.cs.virginia.edu/evans. PS6 (the last one) is posted now and will be due Thursday, April 24. cs302: Theory of Computation

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Lecture 2 Analysis of Algorithms

Lecture 2 Analysis of Algorithms. How to estimate time complexity? Analysis of algorithms Techniques based on Recursions. ACKNOWLEDGEMENTS : Some contents in this lecture source from slides of Yuxi Fu. ROADMAP. How to estimate time complexity? Analysis of algorithms

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Asymptotic Behavior

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Asymptotic Behavior

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David Evans cs.virginia/evans

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David Evans cs.virginia/evans

Lecture 22: P = NP?. David Evans http://www.cs.virginia.edu/evans. CS200: Computer Science University of Virginia Computer Science. Menu. Permuted Sorting What ? Really Means Complexity Classes. Permuted Sorting. A (possibly) really dumb way to sort:

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GQM and data analysis Example from a Norwegian company

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CS21 Decidability and Tractability

CS21 Decidability and Tractability. Lecture 23 March 6 , 2019. Outline. NP-complete problem: max cut (finishing up) The complexity class coNP The complexity class coNP NP The complexity class PSPACE a PSPACE-complete problem. MAX CUT.

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An overview of lecture 8

An overview of lecture 8. When is a problem parallelizable? The complexity classes P and NC and the notion of P-completeness. The Circuit Value Problem is P-complete. When is a problem parallelizable?.

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NP-Completeness

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NP-Completeness

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NP-Completeness

NP-Completeness. Presentation for use with the textbook, Algorithm Design and Applications , by M. T. Goodrich and R. Tamassia, Wiley, 2015. x. x. x. x. x. x. x. x. 1. 1. 2. 2. 3. 3. 4. 4. 12. 22. 32. 11. 13. 21. 23. 31. 33. Input size, n

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Sum this up for me

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Umans Complexity Theory Lectures

Umans Complexity Theory Lectures. Lecture 2a: Reductions & Completeness. Complexity Classes. Back to complexity classes: TIME(T(n)) = languages decidable by a multi-tape TM in at most T(n) steps, where n is the input length, and T : N ? N

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Lecture 22. Time of DTM

Lecture 22. Time of DTM. Time of DTM. Time M (x) = # of moves that DTM M takes on input x. Time M (x) < infinity iff x ? L(M). Time Bound. M is said to have a time bound t(n) if for every x with |x| < n, Time M (x) < max {n+1, t(n)}. Theorem.

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