'O n3' diaporamas de présentation

Global Constraints

Global Constraints . Toby Walsh NICTA and University of New South Wales www.cse.unsw.edu.au/~tw. Quick advert. UNSW is in Sydney Regularly voted in top 10 cities in World UNSW is one of top universities in Australia In top 100 universities in world Talk to me about our PhD programme!

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Algorithms

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A Snapshot on the use of Evolutionary Algorithms for Parameter Optimization: Milestones and Current Trends

A Snapshot on the use of Evolutionary Algorithms for Parameter Optimization: Milestones and Current Trends. Francisco Herrera Research Group on Soft Computing and Information Intelligent Systems (SCI 2 S) http://sci2s.ugr.es Dept . of Computer Science and A.I.

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Growth of Functions

Growth of Functions. CS/APMA 202 Rosen section 2.2 Aaron Bloomfield. How does one measure algorithms. We can time how long it takes a computer What if the computer is doing other things? And what happens if you get a faster computer?

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Image Warping and Morphing

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Computational Geometry

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Directed Graphs

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Pointer Analysis for Multithreaded Programs

Pointer Analysis for Multithreaded Programs. Radu Rugina and Martin Rinard M I T Laboratory for Computer Science. Outline. Example Review of Pointer Analysis for Sequential Programs Pointer Analysis for Multithreaded Programs Experimental Results Conclusions. R. Rugina, M. Rinard.

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Complexity

Complexity. Bryce Boe 2013/10/21 CS24, Fall 2013. Outline. Compiler Review Project 1 Questions Complexity ( Big-O) C++?. Compiler Review. What does the following produce?. clang foobar.c. a.out (executable). What does the following produce?. clang -c foobar.c. foobar.o

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Algorithms

Algorithms. Problems, Algorithms, Programs. 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. NOT necessarily tied to computers.

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Analysis of Algorithms

Analysis of Algorithms. The Non-recursive Case. Except as otherwise noted, the content of this presentation is licensed under the Creative Commons Attribution 2.5 License. . Key Topics:. Introduction Generalizing Running Time Doing a Timing Analysis Big-Oh Notation Big-Oh Operations

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Reduction between Transitive Closure & Boolean Matrix Multiplication

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DP algorithms for all-pairs Shortest Path

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Graph Partitioning

Graph Partitioning. Problem Kernighan and Lin Algorithm Presentation based on http://www.comp.nus.edu.sg/~cs5234/2007-08/Lectures/L06/L06-Graph-Partitioning.ppt. Sparse Matrix partitioning. Graph Segmentation. To partition N into 2 k parts

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Complexity Analysis (Part II )

Complexity Analysis (Part II ). Asymptotic Analysis. Big-O Notation: More Details. Order Arithmetic Rules. Big-O Computation: Improved Guide lines. Require Time. n 0. Input size. Asymptotic Analysis. The Big-O notation is typically written as: f(n) = O(g(n)) .

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Temporal Constraint Propagation (Non-Preemptive Case)

Temporal Constraint Propagation (Non-Preemptive Case). Outline. Variables Relations between the variables Temporal constraints Time bounds Minimal and maximal distances between time points. Variables (definition). Three variables start(A) end(A) duration(A) for each activity A.

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Protein Sequence Classification Using Neighbor-Joining Method

Protein Sequence Classification Using Neighbor-Joining Method. Bo Liu. Overview. Given: A group of sequences, they have somewhat similarity between each other and same protein function. Input: One unknown function sequence Output: If this sequence belongs to this protein cluster. .

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Exhaustive Search (ES):

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