http://servo.ad.wlu.edu/dokuwiki/ 2026-04-17T22:36:07+00:00 http://servo.ad.wlu.edu/dokuwiki/ http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png text/html 2014-01-15T04:03:49+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter1?rev=1389758629&do=diff Chapter 1 My notes on the Preface & Chapter 1 readings Preface The ideas surrounding algorithm analysis are important and pervasive to a variety of disciplines, and a firm understanding of these ideas and their related problems offer us an important mode through which we can understand computer science. Algorithm design is about both finding an elegant mathematical representation of a problem, and then using algorithm design patterns to solve that problem. A quote I especially like from this … text/html 2014-01-22T02:13:07+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter2?rev=1390356787&do=diff Chapter 2 My notes on Chapter 2 readings 2.1: Computational Tractability * We define the efficiency of an algorithm as its worst-case performance in terms of running time compared to the time necessary for a brute-force search, and generally aim to achieve polynomial running time over other sorts of runtimes. While the difference between an n^2 algorithm and an n^5 algorithm may seem big, we'd obviously significantly prefer n^5 over 2^n running time. text/html 2014-02-12T07:33:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter3?rev=1392190401&do=diff Chapter 3 My notes on Chapter 3 readings 3.1: Basic Definitions & Applications * Graphs are the coolest. A graph is a collection V of vertices and a collection E of edges such that each edge e∈E joins exactly two vertices in V. * They can be used to model a lot of things: text/html 2014-03-05T06:04:43+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter4?rev=1393999483&do=diff Chapter 4 My notes on Chapter 4 readings Intro & 4.1: Interval Scheduling * A greedy algorithm uses a sum of local optimizations to make a global optimization. * We can show optimality by showing that greedy stays ahead or by making an exchange argument to show that the greedy solution and the optimal solution are equivalent. text/html 2014-03-12T02:35:44+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter5?rev=1394591744&do=diff Chapter 5 Divide & Conquer notes Intro & 5.1: Interval Scheduling * Divide & conquer algorithms are characterized by the fact that they divide the input into smaller groups and solve the problem recursively. * They're often used to get polytime to a lower polynomial. text/html 2014-03-26T04:25:06+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter6?rev=1395807906&do=diff Chapter 6 Dynamic Programming notes Intro & 6.1: Weighted Interval Scheduling * Divide & conquer algorithms are characterized by the fact that they divide the input into smaller groups and solve the problem recursively. Unlike D&C, however, it tends to require text/html 2014-04-02T05:20:53+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/chapter7?rev=1396416053&do=diff Chapter 7 Network Flow notes Intro & 7.1: Maximum Flow & Ford-Fulkerson * Network flow problems include the bipartite matching problem, among others. Networks are graphs whose edges carry something and whose nodes facilitate passing traffic between edges. text/html 2014-04-02T03:26:39+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2014/journals/haley/home?rev=1396409199&do=diff Haley's 211 Journals * Chapter 1: Introduction * Chapter 2: Algorithm Analysis * Chapter 3: Graphs * Chapter 4: Greedy Algorithms * Chapter 5: Divide & Conquer * Chapter 6: Dynamic Programming * Chapter 7: Network Flow