Algorithm Design

Name: Algorithm Design
Author: Jon Kleinberg, Eva Tardos
ISBN: 9780321295354

by Jon Kleinberg, Eva Tardos

3 (2)

Paperback

Algorithm Design

by Jon Kleinberg, Eva Tardos

3 (2)

Paperback

Condition

Overview

Algorithm Design 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. August 6, 2009 Author, Jon Kleinberg, was recently cited in the New York Times for his statistical analysis research in the Internet age.

FormatPaperback

LanguageEnglish

PublisherPearson Education

Publication DateMar. 16th, 2005

Editiondesign Edition

ISBN-139780321295354

Dimensions8.20 x 9.00 x 1.90 inches

ISBN-100321295358

Shipping Weight3.85 lbs

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Reader Reviews for Algorithm Design

About the Authors	p. v
Preface	p. xiii
Introduction: Some Representative Problems	p. 1
A First Problem: Stable Matching	p. 1
Five Representative Problems	p. 12
Solved Exercises	p. 19
Exercises	p. 22
Notes and Further Reading	p. 28
Basics of Algorithm Analysis	p. 29
Computational Tractability	p. 29
Asymptotic Order of Growth	p. 35
Implementing the Stable Matching Algorithm Using Lists and Arrays	p. 42
A Survey of Common Running Times	p. 47
A More Complex Data Structure: Priority Queues	p. 57
Solved Exercises	p. 65
Exercises	p. 67
Notes and Further Reading	p. 70
Graphs	p. 73
Basic Definitions and Applications	p. 73
Graph Connectivity and Graph Traversal	p. 78
Implementing Graph Traversal Using Queues and Stacks	p. 87
Testing Bipartiteness: An Application of Breadth-First Search	p. 94
Connectivity in Directed Graphs	p. 97
Directed Acyclic Graphs and Topological Ordering	p. 99
Solved Exercises	p. 104
Exercises	p. 107
Notes and Further Reading	p. 112
Greedy Algorithms	p. 115
Interval Scheduling: The Greedy Algorithm Stays Ahead	p. 116
Scheduling to Minimize Lateness: An Exchange Argument	p. 125
Optimal Caching: A More Complex Exchange Argument	p. 131
Shortest Paths in a Graph	p. 137
The Minimum Spanning Tree Problem	p. 142
Implementing Kruskal's Algorithm: The Union-Find Data Structure	p. 151
Clustering	p. 157
Huffman Codes and Data Compression	p. 161
Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm	p. 177
Solved Exercises	p. 183
Exercises	p. 188
Notes and Further Reading	p. 205
Divide and Conquer	p. 209
A First Recurrence: The Mergesort Algorithm	p. 210
Further Recurrence Relations	p. 214
Counting Inversions	p. 221
Finding the Closest Pair of Points	p. 225
Integer Multiplication	p. 231
Convolutions and the Fast Fourier Transform	p. 234
Solved Exercises	p. 242
Exercises	p. 246
Notes and Further Reading	p. 249
Dynamic Programming	p. 251
Weighted Interval Scheduling: A Recursive Procedure	p. 252
Principles of Dynamic Programming: Memoization or Iteration over Subproblems	p. 258
Segmented Least Squares: Multi-way Choices	p. 261
Subset Sums and Knapsacks: Adding a Variable	p. 266
RNA Secondary Structure: Dynamic Programming over Intervals	p. 272
Sequence Alignment	p. 278
Sequence Alignment in Linear Space via Divide and Conquer	p. 284
Shortest Paths in a Graph	p. 290
Shortest Paths and Distance Vector Protocols	p. 297
Negative Cycles in a Graph	p. 301
Solved Exercises	p. 307
Exercises	p. 312
Notes and Further Reading	p. 335
Network Flow	p. 337
The Maximum-Flow Problem and the Ford-Fulkerson Algorithm	p. 338
Maximum Flows and Minimum Cuts in a Network	p. 346
Choosing Good Augmenting Paths	p. 352
The Preflow-Push Maximum-Flow Algorithm	p. 357
A First Application: The Bipartite Matching Problem	p. 367
Disjoint Paths in Directed and Undirected Graphs	p. 373
Extensions to the Maximum-Flow Problem	p. 378
Survey Design	p. 384
Airline Scheduling	p. 387
Image Segmentation	p. 391
Project Selection	p. 396
Baseball Elimination	p. 400
A Further Direction: Adding Costs to the Matching Problem	p. 404
Solved Exercises	p. 411
Exercises	p. 415
Notes and Further Reading	p. 448
NP and Computational Intractability	p. 451
Polynomial-Time Reductions	p. 452
Reductions via "Gadgets": The Satisfiability Problem	p. 459
Efficient Certification and the Definition of NP	p. 463
NP-Complete Problems	p. 466
Sequencing Problems	p. 473
Partitioning Problems	p. 481
Graph Coloring	p. 485
Numerical Problems	p. 490
Co-NP and the Asymmetry of NP	p. 495
A Partial Taxonomy of Hard Problems	p. 497
Solved Exercises	p. 500
Exercises	p. 505
Notes and Further Reading	p. 529
PSPACE: A Class of Problems beyond NP	p. 531
PSPACE	p. 531
Some Hard Problems in PSPACE	p. 533
Solving Quantified Problems and Games in Polynomial Space	p. 536
Solving the Planning Problem in Polynomial Space	p. 538
Proving Problems PSPACE-Complete	p. 543
Solved Exercises	p. 547
Exercises	p. 550
Notes and Further Reading	p. 551
Extending the Limits of Tractability	p. 553
Finding Small Vertex Covers	p. 554
Solving NP-Hard Problems on Trees	p. 558
Coloring a Set of Circular Arcs	p. 563
Tree Decompositions of Graphs	p. 572
Constructing a Tree Decomposition	p. 584
Solved Exercises	p. 591
Exercises	p. 594
Notes and Further Reading	p. 598
Approximation Algorithms	p. 599
Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem	p. 600
The Center Selection Problem	p. 606
Set Cover: A General Greedy Heuristic	p. 612
The Pricing Method: Vertex Cover	p. 618
Maximization via the Pricing Method: The Disjoint Paths Problem	p. 624
Linear Programming and Rounding: An Application to Vertex Cover	p. 630
Load Balancing Revisited: A More Advanced LP Application	p. 637
Arbitrarily Good Approximations: The Knapsack Problem	p. 644
Solved Exercises	p. 649
Exercises	p. 651
Notes and Further Reading	p. 659
Local Search	p. 661
The Landscape of an Optimization Problem	p. 662
The Metropolis Algorithm and Simulated Annealing	p. 666
An Application of Local Search to Hopfield Neural Networks	p. 671
Maximum-Cut Approximation via Local Search	p. 676
Choosing a Neighbor Relation	p. 679
Classification via Local Search	p. 681
Best-Response Dynamics and Nash Equilibria	p. 690
Solved Exercises	p. 700
Exercises	p. 702
Notes and Further Reading	p. 705
Randomized Algorithms	p. 707
A First Application: Contention Resolution	p. 708
Finding the Global Minimum Cut	p. 714
Random Variables and Their Expectations	p. 719
A Randomized Approximation Algorithm for MAX 3-SAT	p. 724
Randomized Divide and Conquer: Median-Finding and Quicksort	p. 727
Hashing: A Randomized Implementation of Dictionaries	p. 734
Finding the Closest Pair of Points: A Randomized Approach	p. 741
Randomized Caching	p. 750
Chernoff Bounds	p. 758
Load Balancing	p. 760
Packet Routing	p. 762
Background: Some Basic Probability Definitions	p. 769
Solved Exercises	p. 776
Exercises	p. 782
Notes and Further Reading	p. 793
Epilogue: Algorithms That Run Forever	p. 795
References	p. 805
Index	p. 815
Table of Contents provided by Ingram. All Rights Reserved.

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Overview

Product Details

FormatPaperback

LanguageEnglish

PublisherPearson Education

Publication DateMar. 16th, 2005

Editiondesign Edition

ISBN-139780321295354

Dimensions8.20 x 9.00 x 1.90 inches

ISBN-100321295358

Shipping Weight3.85 lbs

Reviews

About the Authors	p. v
Preface	p. xiii
Introduction: Some Representative Problems	p. 1
A First Problem: Stable Matching	p. 1
Five Representative Problems	p. 12
Solved Exercises	p. 19
Exercises	p. 22
Notes and Further Reading	p. 28
Basics of Algorithm Analysis	p. 29
Computational Tractability	p. 29
Asymptotic Order of Growth	p. 35
Implementing the Stable Matching Algorithm Using Lists and Arrays	p. 42
A Survey of Common Running Times	p. 47
A More Complex Data Structure: Priority Queues	p. 57
Solved Exercises	p. 65
Exercises	p. 67
Notes and Further Reading	p. 70
Graphs	p. 73
Basic Definitions and Applications	p. 73
Graph Connectivity and Graph Traversal	p. 78
Implementing Graph Traversal Using Queues and Stacks	p. 87
Testing Bipartiteness: An Application of Breadth-First Search	p. 94
Connectivity in Directed Graphs	p. 97
Directed Acyclic Graphs and Topological Ordering	p. 99
Solved Exercises	p. 104
Exercises	p. 107
Notes and Further Reading	p. 112
Greedy Algorithms	p. 115
Interval Scheduling: The Greedy Algorithm Stays Ahead	p. 116
Scheduling to Minimize Lateness: An Exchange Argument	p. 125
Optimal Caching: A More Complex Exchange Argument	p. 131
Shortest Paths in a Graph	p. 137
The Minimum Spanning Tree Problem	p. 142
Implementing Kruskal's Algorithm: The Union-Find Data Structure	p. 151
Clustering	p. 157
Huffman Codes and Data Compression	p. 161
Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm	p. 177
Solved Exercises	p. 183
Exercises	p. 188
Notes and Further Reading	p. 205
Divide and Conquer	p. 209
A First Recurrence: The Mergesort Algorithm	p. 210
Further Recurrence Relations	p. 214
Counting Inversions	p. 221
Finding the Closest Pair of Points	p. 225
Integer Multiplication	p. 231
Convolutions and the Fast Fourier Transform	p. 234
Solved Exercises	p. 242
Exercises	p. 246
Notes and Further Reading	p. 249
Dynamic Programming	p. 251
Weighted Interval Scheduling: A Recursive Procedure	p. 252
Principles of Dynamic Programming: Memoization or Iteration over Subproblems	p. 258
Segmented Least Squares: Multi-way Choices	p. 261
Subset Sums and Knapsacks: Adding a Variable	p. 266
RNA Secondary Structure: Dynamic Programming over Intervals	p. 272
Sequence Alignment	p. 278
Sequence Alignment in Linear Space via Divide and Conquer	p. 284
Shortest Paths in a Graph	p. 290
Shortest Paths and Distance Vector Protocols	p. 297
Negative Cycles in a Graph	p. 301
Solved Exercises	p. 307
Exercises	p. 312
Notes and Further Reading	p. 335
Network Flow	p. 337
The Maximum-Flow Problem and the Ford-Fulkerson Algorithm	p. 338
Maximum Flows and Minimum Cuts in a Network	p. 346
Choosing Good Augmenting Paths	p. 352
The Preflow-Push Maximum-Flow Algorithm	p. 357
A First Application: The Bipartite Matching Problem	p. 367
Disjoint Paths in Directed and Undirected Graphs	p. 373
Extensions to the Maximum-Flow Problem	p. 378
Survey Design	p. 384
Airline Scheduling	p. 387
Image Segmentation	p. 391
Project Selection	p. 396
Baseball Elimination	p. 400
A Further Direction: Adding Costs to the Matching Problem	p. 404
Solved Exercises	p. 411
Exercises	p. 415
Notes and Further Reading	p. 448
NP and Computational Intractability	p. 451
Polynomial-Time Reductions	p. 452
Reductions via "Gadgets": The Satisfiability Problem	p. 459
Efficient Certification and the Definition of NP	p. 463
NP-Complete Problems	p. 466
Sequencing Problems	p. 473
Partitioning Problems	p. 481
Graph Coloring	p. 485
Numerical Problems	p. 490
Co-NP and the Asymmetry of NP	p. 495
A Partial Taxonomy of Hard Problems	p. 497
Solved Exercises	p. 500
Exercises	p. 505
Notes and Further Reading	p. 529
PSPACE: A Class of Problems beyond NP	p. 531
PSPACE	p. 531
Some Hard Problems in PSPACE	p. 533
Solving Quantified Problems and Games in Polynomial Space	p. 536
Solving the Planning Problem in Polynomial Space	p. 538
Proving Problems PSPACE-Complete	p. 543
Solved Exercises	p. 547
Exercises	p. 550
Notes and Further Reading	p. 551
Extending the Limits of Tractability	p. 553
Finding Small Vertex Covers	p. 554
Solving NP-Hard Problems on Trees	p. 558
Coloring a Set of Circular Arcs	p. 563
Tree Decompositions of Graphs	p. 572
Constructing a Tree Decomposition	p. 584
Solved Exercises	p. 591
Exercises	p. 594
Notes and Further Reading	p. 598
Approximation Algorithms	p. 599
Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem	p. 600
The Center Selection Problem	p. 606
Set Cover: A General Greedy Heuristic	p. 612
The Pricing Method: Vertex Cover	p. 618
Maximization via the Pricing Method: The Disjoint Paths Problem	p. 624
Linear Programming and Rounding: An Application to Vertex Cover	p. 630
Load Balancing Revisited: A More Advanced LP Application	p. 637
Arbitrarily Good Approximations: The Knapsack Problem	p. 644
Solved Exercises	p. 649
Exercises	p. 651
Notes and Further Reading	p. 659
Local Search	p. 661
The Landscape of an Optimization Problem	p. 662
The Metropolis Algorithm and Simulated Annealing	p. 666
An Application of Local Search to Hopfield Neural Networks	p. 671
Maximum-Cut Approximation via Local Search	p. 676
Choosing a Neighbor Relation	p. 679
Classification via Local Search	p. 681
Best-Response Dynamics and Nash Equilibria	p. 690
Solved Exercises	p. 700
Exercises	p. 702
Notes and Further Reading	p. 705
Randomized Algorithms	p. 707
A First Application: Contention Resolution	p. 708
Finding the Global Minimum Cut	p. 714
Random Variables and Their Expectations	p. 719
A Randomized Approximation Algorithm for MAX 3-SAT	p. 724
Randomized Divide and Conquer: Median-Finding and Quicksort	p. 727
Hashing: A Randomized Implementation of Dictionaries	p. 734
Finding the Closest Pair of Points: A Randomized Approach	p. 741
Randomized Caching	p. 750
Chernoff Bounds	p. 758
Load Balancing	p. 760
Packet Routing	p. 762
Background: Some Basic Probability Definitions	p. 769
Solved Exercises	p. 776
Exercises	p. 782
Notes and Further Reading	p. 793
Epilogue: Algorithms That Run Forever	p. 795
References	p. 805
Index	p. 815
Table of Contents provided by Ingram. All Rights Reserved.

Algorithm Design

3 (2)

Paperback

See All Available Copies

Algorithm Design

3 (2)

Paperback

See All Available Copies

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