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        <description>Week 1

Chapter 0: Preface

Algorithms are everywhere.  By using algorithms, we can not only find solutions to difficult problems but also do so efficiently and prove that our findings are accurate.  If we work hard, we can find solutions to problems as</description>
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        <dc:date>2012-03-07T03:45:43+00:00</dc:date>
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        <description>Week 2

Chapter 2: Basics of Algorithm Analysis

Arrays and Lists

Algorithms tend to abstract away the method for storing data that is needed to actually run the algorithm.  In order to run the algorithm on a computer, we need a way to transform our algorithm into a form that a computer can recognize.  Luckily, most of the steps in the algorithm are usually easily transferrable, but the implementation of data structures is not specified in the algorithm and so is left up to the programmer to de…</description>
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        <description>Week 3

Chapter 3: Graphs

3.1: Basic Definitions and Applications

An undirected graph is defined to be a set of nodes and a set of edges.  Each edge is defined to be a set of exactly two nodes that represent a direct relationship between them.
A directed graph</description>
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        <dc:date>2012-02-15T05:06:01+00:00</dc:date>
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        <description>Week 4

Readings

Chapter 3: Graphs

3.5: Connectivity in Directed Graphs

As noted in section 3.1, undirected graphs are just a special case of directed graphs in that an undirected has a set of edges such that for every edge (u, v) there also exists an edge</description>
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        <description>Week 5-6

Chapter Scores

	*  Readability Score: 7/10
	*  Interest Score: 9/10

Readings

Chapter 4: Greedy Algorithms

4.1: Interval Scheduling

The interval scheduling problem involves a shared resource and a set of requests.  Each request wants to use that resource from a certain point in time to a certain ending point in time.  When a request is using a resource, no other request can be using the resource during any part of its time slot, meaning that there can be no more than one request sc…</description>
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        <description>Week 7

Chapter Scores

	*  Readability Score: 7/10
	*  Interest Score: 4/10

Readings

Chapter 5: Divide and Conquer

5.1: A First Recurrence - The Mergesort Algorithm

This section of the reading describes mergesort as the most canonical divide-and-conquer algorithm.  A</description>
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        <dc:date>2012-03-14T03:27:50+00:00</dc:date>
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        <title>week_8</title>
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        <description>Week 8

Chapter Scores

	*  Readability Score: 4 / 10 
	*  Interest Score: 7 / 10 

Readings

Chapter 5: Divide and Conquer

5.3: Counting Inversions

Section 5.3 Summary

5.4: Finding the Closest Pair of Points

Problem: Given n points on an X,Y coordinate plane, find the two points that are the smallest distance away from each other than to any other two points.</description>
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        <dc:date>2012-03-28T04:04:27+00:00</dc:date>
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        <description>Week 9

Chapter Scores
 Readability Score  6 / 10     Interest Score  8 / 10   
Readings

Chapter 6: Dynamic Programming

6.1: Weighted Interval Scheduling

The weighted interval scheduling problem is a lot like the unweighted interval scheduling problem except that each task to be scheduled has a priority or weight to it and we want to schedule jobs such that we have the largest possible weight.  With so many variables and components to consider and take into account, a</description>
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        <dc:date>2012-04-04T05:55:48+00:00</dc:date>
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        <description>Week 10

Chapter Scores
 Readability Score  8 / 10     Interest Score  9 / 10    
Readings

Chapter 7: Network Flow

7.1: The Maximum-Flow Problem and the Ford-Fulkerson Algorithm

A flow network is a specific kind of graph that has a node that is the source of some sort of traffic, directed edges indicating the maximum amount of allowed traffic between two nodes, and a node that is the destination of all of the traffic.  The amount of traffic flow coming from the source node must equal the amou…</description>
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