<p>August 6, 2009 <strong>Author, Jon Kleinberg, was recently cited in the <a>New York Times</a> for his statistical analysis research in the Internet age.</strong></p><p><strong><em><strong>Algorithm Design </strong></em></strong>introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.</p>

<ul>
    <li>1 Introduction: Some Representative Problems&nbsp;&nbsp; </li>
    <li>2 Basics of Algorithms Analysis&nbsp;&nbsp; </li>
    <li>3 Graphs&nbsp;&nbsp; </li>
    <li>4 Divide and Conquer&nbsp; </li>
    <li>5&nbsp;Greedy Algorithms </li>
    <li>6 Dynamic Programming&nbsp;&nbsp; </li>
    <li>7 Network Flow&nbsp;&nbsp; </li>
    <li>8 NP and Computational Intractability&nbsp;&nbsp; </li>
    <li>9 PSPACE: A Class of Problems Beyond NP </li>
    <li>10 Extending the Limits of Tractability&nbsp;&nbsp; </li>
    <li>11 Approximation Algorithms&nbsp;&nbsp;&nbsp; </li>
    <li>12 Randomized Algorithms&nbsp;&nbsp; </li>
    <li>13 Local Search&nbsp;&nbsp; </li>
    <li>Epilogue: Algorithms that Run Forever&nbsp; </li>
    <li>References </li>
    <li>Index </li>
</ul>

<p><i><strong>Algorithm Design </strong></i>introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.</p>
<p><strong>The full text downloaded to your computer</strong></p>
<p>With eBooks you can:</p>
<ul>
    <li>search for key concepts, words and phrases </li>
    <li>make highlights and notes as you study </li>
    <li>share your notes with friends </li>
</ul>
<p><strong>eBooks </strong>are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. </p>
<p>Upon purchase, you'll gain instant access to this eBook.</p>
<p><strong><u>Time limit</u></strong></p>
<p>The&nbsp;<strong>eBooks</strong> products do not have an expiry date. You will continue to access your&nbsp;digital&nbsp;ebook&nbsp;products whilst you have your&nbsp;Bookshelf installed.</p>

<p>Algorithm Design<br/>Jon Kleinberg and Eva Tardos<br/><br/>Table of Contents <br/><br/>1 Introduction: Some Representative Problems&nbsp;&nbsp;</p><p>&nbsp;1.1&nbsp;A First Problem: Stable Matching&nbsp;&nbsp;</p><p>&nbsp;1.2&nbsp;Five Representative Problems&nbsp;&nbsp;<br/>&nbsp;Solved Exercises<br/>Excercises<br/>Notes and Further Reading<br/></p><p>&nbsp;</p><p>&nbsp;</p><p>2 Basics of Algorithms Analysis&nbsp;&nbsp;</p><p>&nbsp;2.1 Computational Tractability&nbsp;&nbsp;</p><p>&nbsp;2.2 Asymptotic Order of Growth Notation&nbsp;&nbsp;</p><p>&nbsp;2.3 Implementing the Stable Matching Algorithm using Lists and Arrays</p><p>&nbsp;2.4 A Survey of Common Running Times&nbsp;&nbsp;</p><p>&nbsp;2.5 A More Complex Data Structure: Priority Queues</p><p>&nbsp;Solved Exercises&nbsp;&nbsp;<br/>&nbsp;Exercises&nbsp;&nbsp;<br/>&nbsp;Notes and Further Reading<br/></p><p>&nbsp;</p><p>&nbsp;</p><p>3 Graphs&nbsp;&nbsp;</p><p>&nbsp;3.1 Basic Definitions and Applications&nbsp;&nbsp;</p><p>&nbsp;3.2 Graph Connectivity and Graph Traversal&nbsp;&nbsp;<br/>&nbsp;3.3 Implementing Graph Traversal using Queues and Stacks<br/>&nbsp;3.4 Testing Bipartiteness: An Application of Breadth-First Search&nbsp;&nbsp;<br/>&nbsp;3.5 Connectivity in Directed Graphs&nbsp;&nbsp;<br/>&nbsp;3.6 Directed Acyclic Graphs and Topological Ordering&nbsp;&nbsp;<br/>&nbsp;Solved Exercises&nbsp;&nbsp;<br/>Exercises&nbsp;&nbsp;<br/>&nbsp;Notes and Further Reading</p><p><br/>&nbsp;</p><p>&nbsp;4 Divide and Conquer&nbsp;&nbsp;<br/>&nbsp;4.1 A First Recurrence: The Mergesort Algorithm<br/>&nbsp;4.2 Further Recurrence Relations<br/>&nbsp;4.3 Counting Inversions<br/>&nbsp;4.4 Finding the Closest Pair of Points<br/>&nbsp;4.5 Integer Multiplication<br/>&nbsp;4.6 Convolutions and The Fast Fourier Transform<br/>&nbsp;Solved Exercises<br/>&nbsp;Exercises<br/>&nbsp;Notes and Further Reading<br/></p><p>&nbsp;</p><p>5&nbsp;Greedy Algorithms&nbsp;&nbsp;<br/>&nbsp;5.1 Interval Scheduling: The Greedy Algorithm Stays Ahead&nbsp;&nbsp;<br/>&nbsp;5.2 Scheduling to Minimize Lateness: An Exchange Argument<br/>&nbsp;5.3 Optimal Caching: A More Complex Exchange Argument<br/>&nbsp;5.4 Shortest Paths in a Graph&nbsp;&nbsp;<br/>&nbsp;5.5 The Minimum Spanning Tree Problem&nbsp;&nbsp;<br/>&nbsp;5.6 Implementing Kruskal's Algorithm: The Union-Find Data Structure<br/>&nbsp;5.7 Clustering&nbsp;&nbsp;<br/>&nbsp;5.8 Huffman Codes and the Problem of Data Compression<br/>*5.9 Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm&nbsp;&nbsp;<br/>&nbsp;Solved Exercises<br/>&nbsp;Excercises<br/>&nbsp;Notes and Further Reading</p><p>&nbsp;</p><p>6 Dynamic Programming&nbsp;&nbsp;<br/>&nbsp;6.1 Weighted Interval Scheduling: A Recursive Procedure&nbsp;&nbsp;<br/>6.2 Weighted Interval Scheduling: Iterating over Sub-Problems&nbsp;&nbsp;<br/>&nbsp;6.3 Segmented Least Squares: Multi-way Choices&nbsp;&nbsp;<br/>&nbsp;6.4 Subset Sums and Knapsacks: Adding a Variable&nbsp;&nbsp;<br/>&nbsp;6.5 RNA Secondary Structure: Dynamic Programming Over Intervals&nbsp;&nbsp;<br/>&nbsp;6.6 Sequence Alignment&nbsp;&nbsp;<br/>&nbsp;6.7 Sequence Alignment in Linear Space<br/>&nbsp;6.8 Shortest Paths in a Graph&nbsp;&nbsp;<br/>&nbsp;6.9 Shortest Paths and Distance Vector Protocols&nbsp;&nbsp;<br/>*6.10 Negative Cycles in a Graph&nbsp;&nbsp;</p><p>Solved Exercises<br/>Exercises<br/>Notes and Further Reading<br/></p><p>&nbsp;</p><p>&nbsp;</p><p>7 Network Flow&nbsp;&nbsp;<br/>&nbsp;7.1 The Maximum Flow Problem and the Ford-Fulkerson Algorithm<br/>&nbsp;7.2 Maximum Flows and Minimum Cuts in a Network&nbsp;&nbsp;<br/>&nbsp;7.3 Choosing Good Augmenting Paths&nbsp;&nbsp;<br/>*7.4 The Preflow-Push Maximum Flow Algorithm&nbsp;&nbsp;<br/>&nbsp;7.5 A First Application: The Bipartite Matching Problem<br/>&nbsp;7.6 Disjoint Paths in Directed and Undirected Graphs<br/>&nbsp;7.7 Extensions to the Maximum Flow Problem&nbsp;&nbsp;<br/>&nbsp;7.8 Survey Design&nbsp;&nbsp;<br/>&nbsp;7.9 Airline Scheduling&nbsp;&nbsp;<br/>&nbsp;7.10 Image Segmentation&nbs

<p><i><strong>Algorithm Design </strong></i>introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.</p>

Jon Kleinberg

Eva Tardos

A digital version of the text you can personalize and read online or offline.

eTextbook

Algorithm Design

Algorithm Design, Pearson New International Edition

This product is a bound, printed text book.

Print

Paperback

Algorithm Design, Pearson New International Edition, 1st edition

Access details

Features

Details