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    Technology

    Algorithm Design and Analysis

    The purpose of this undergraduate course is to introduce fundamental techniques and viewpoints for the design and the analysis of efficient computer algorithms, and to study important specific algorithms. The course relies heavily on mathematics and mathematical thinking in two ways: first as a way of proving properties about particular algorithms such as termination, and correctness; and second, as a way of establishing bounds on the worst case (or average case) use of some resource, usually time, by a specific algorithm. The course covers some randomized algorithms as well as deterministic algorithms.

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    Copyright: © Copyright The Regents of the University of California, Davis campus, 2012. All Rights Reserved.

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    Latest Episodes:
    Greedy algorithms: Picking largest set of non-overlapping intervals Oct 13, 2010
    Show notes

    For Lecture 9, Gusfield starts discussion of greedy algorithms: Picking the largest number of non-overlapping intervals on a line.

    Expected number of comparisons in randomized select Oct 11, 2010
    Show notes

    In Lecture 8, Gusfield completes his analysis of the expected number of comparisons in randomized version of Select(S,k) as a function of |S|. The expected number is at most 8|S|.

    More on randomized selection and median finding Oct 08, 2010
    Show notes

    During Lecture 7, students learn more on randomized selection and median finding: algorithm and start of analysis.

    Fast integer multiplication, randomized selection and median finding Oct 06, 2010
    Show notes

    In Lecture 6, Gusfield finishes the discussion of integer multiplication by divide and conquer. He then starts randomized selection and median finding.

    Counting inversions; Fast integer multiplication Oct 04, 2010
    Show notes

    Lecture 5: Gusfield lectures about counting the number of inversions in a permutation. He introduces fast integer multiplication by divide and conquer.

    A more complex recurrence relation and counting inversions Oct 01, 2010
    Show notes

    In Lecture 4, students learn about solving a more complex recurrence relation by unwrapping. Gusfield also addresses the problem of counting inversions in a permutation.

    Time analysis of Mergesort Sep 29, 2010
    Show notes

    In Lecture 3, Gusfield gives the worst-case analysis of MergeSort by setting up a recurrence relation and solving it by unwrapping.

    Big-Oh, Omega and Theta notation Sep 27, 2010
    Show notes

    In Lecture 2, Gusfield discusses Big-Oh, Omega and Theta notation. He describes Mergesort and Merge and the start of their time analysis.

    Introduction to the course and algorithm complexity Sep 24, 2010
    Show notes

    This is the course introduction about algorithm complexity, including what "worst case running time" means and how it is measured.

    Introduction to the videos Sep 23, 2010
    Show notes

    This video shows the URL for printed material that accompanies the course, and a URL for more advanced lectures on material that overlaps and extends the course. The URL for printed course material is: www.cs.ucdavis.edu/~gusfield/itunesU The URL for more advanced lectures is: www.cs.ucdavis.edu/~gusfield/cs222f07/videolist.html

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