http://servo.ad.wlu.edu/dokuwiki/ 2026-05-11T23:27:05+00:00 http://servo.ad.wlu.edu/dokuwiki/ http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png text/html 2018-01-28T21:49:28+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter1?rev=1517176168&do=diff Chapter 1 1.1: Stable Matching Problem Chapter one was very easy to read, as it reinforced up what we had learned in class. In chapter 1.1, the authors discussed the Stable Matching Problem, which has many applications beyond those discussed in the textbook. When learning about the process behind the Stable Matching Problem in class, it made a lot of sense. Reading it in the textbook helped to reinforce my understanding. text/html 2018-01-28T22:37:48+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter2?rev=1517179068&do=diff Chapter 2 2.1: Computational Tractability This section reminded me of what we learned in the CSCI 112 course at W&L. This section focused on runtime and memory allocation in terms of efficiency. It was fairly straightforward and easy to read. Reading about runtime for algorithms, it reinforced what I had learned in my previous computer science courses (big O notation). The methodology behind finding efficiency is to start by analyzing worst-case run times. For example, in the stable matching p… text/html 2018-02-07T00:55:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter3?rev=1517964905&do=diff Chapter 3: Graphs 3.1: Basic Definitions and Applications This chapter was very easy to read, and I would score it about a 7 on a scale from 1-10 on readability. This section defined graphs and outlined some common uses for them. A graph is made up of a collection V of nodes and a collection E of edges, which text/html 2018-03-12T23:28:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter4?rev=1520897301&do=diff Chapter 4: Greedy Algorithms Introduction This section opens up by discussion some of the merits of being ‘greedy’. It defines a greedy algorithm to be one that can build a solution using small steps, each step making a decision that will optimize the solution. Various greedy algorithms can be created for the same problem. The success of a greedy algorithm helps to imply that there exists a certain ‘rule’ that can be applied to the decisions at each step which one can use to create an optimal … text/html 2018-03-13T02:12:26+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter5?rev=1520907146&do=diff Chapter 5: Divide and Conquer 5.1: A First Recurrence: The Mergesort Algorithm The Mergesort Algorithm shows the general approach to analyzing divide-and-conquer algorithms. Mergesort can be summarized as follows: “Divide the input into two pieces of equal size; solve the two subproblems on these pieces separately by recursion; and then combine the two results into an overall solution, spending only linear time for the initial division and final recombining text/html 2018-03-26T03:03:54+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter6?rev=1522033434&do=diff Chapter 6: Dynamic Programming 6.1: Weighted Interval Scheduling: A Recursive Procedure We can create a more general version of the interval scheduling problem, solving it without using a greedy algorithm. Using Dynamic Programming, we can account for the weights not all having the same value. The solution using dynamic programming involves a recursive algorithm. We still have n requests with a start time and a finish time, however, each interval has a value. Two intervals are still compatible… text/html 2018-04-02T03:44:08+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/chapter7?rev=1522640648&do=diff Chapter 7: Network Flow 7.1: The Maximum-Flow Problem and the Ford-Fulkerson Algorithm This section discusses modeling networks involving capacities, source nodes, sink nodes, and the direction of transmission. This transmission is considered flow, from the source nodes through the edges to the sink nodes. A flow network must have a non-negative capacity at each edge, a source node (s), and a sink node (t). All other nodes are considered internal nodes. A flow must have two conditions. First, … text/html 2018-01-15T19:23:18+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/preface?rev=1516044198&do=diff Preface xiii and xiv While the first two pages of Preface were brief, they were very informative. Algorithms have applications in an infinite number of fields. In fact, it was described in this chapter that algorithms are considered a “powerful lens text/html 2018-04-01T23:04:54+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2018/journals/cohene/home/sidebar?rev=1522623894&do=diff Emily's Wiki * Preface * Chapter 1 * Chapter 2 * Chapter 3 * Chapter 4 * Chapter 5 * Chapter 6 * Chapter 7 ---------- <- Emily's Wiki <- CSCI 211: Algorithm Design and Analysis