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The Resource Algorithm design and applications, Michael T. Goodrich, Department of Information and Computer Science, University of California, Irvine, Roberto Tamassia, Department of Computer Science, Brown University

Algorithm design and applications, Michael T. Goodrich, Department of Information and Computer Science, University of California, Irvine, Roberto Tamassia, Department of Computer Science, Brown University

Label
Algorithm design and applications
Title
Algorithm design and applications
Statement of responsibility
Michael T. Goodrich, Department of Information and Computer Science, University of California, Irvine, Roberto Tamassia, Department of Computer Science, Brown University
Creator
Contributor
Author
Subject
Language
eng
Cataloging source
DLC
http://library.link/vocab/creatorName
Goodrich, Michael T
Index
index present
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1960-
http://library.link/vocab/relatedWorkOrContributorName
Tamassia, Roberto
http://library.link/vocab/subjectName
  • Computer algorithms
  • Data structures (Computer science)
Label
Algorithm design and applications, Michael T. Goodrich, Department of Information and Computer Science, University of California, Irvine, Roberto Tamassia, Department of Computer Science, Brown University
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
  • A Case Study in Algorithm Analysis
  • A Lower Bound on Comparison-Based Sorting
  • 8.4.
  • Exercises
  • 9.
  • Fast Sorting and Selection
  • 9.1.
  • Bucket-Sort and Radix-Sort
  • 9.2.
  • Selection
  • 9.3.
  • 1.4.
  • Weighted Medians
  • 9.4.
  • Exercises
  • pt. III
  • Fundamental Techniques
  • 10.
  • The Greedy Method
  • 10.1.
  • The Fractional Knapsack Problem
  • 10.2.
  • Amortization
  • Task Scheduling
  • 10.3.
  • Text Compression and Huffman Coding
  • 10.4.
  • Exercises
  • 11.
  • Divide-and-Conquer
  • 11.1.
  • Recurrences and the Master Theorem
  • 11.2.
  • 1.5.
  • Integer Multiplication
  • 11.3.
  • Matrix Multiplication
  • 11.4.
  • The Maxima-Set Problem
  • 11.5.
  • Exercises
  • 12.
  • Dynamic Programming
  • 12.1.
  • Exercises
  • Matrix Chain-Products
  • 12.2.
  • The General Technique
  • 12.3.
  • Telescope Scheduling
  • 12.4.
  • Game Strategies
  • 12.5.
  • The Longest Common Subsequence Problem
  • 12.6.
  • pt. I
  • The 0-1 Knapsack Problem
  • 12.7.
  • Exercises
  • 13.
  • Graphs and Traversals
  • 13.1.
  • Graph Terminology and Representations
  • 13.2.
  • Depth-First Search
  • 13.3.
  • Data Structures
  • Breadth-First Search
  • 13.4.
  • Directed Graphs
  • 13.5.
  • Biconnected Components
  • 13.6.
  • Exercises
  • pt. IV
  • Graph Algorithms
  • 14.
  • 2.
  • Shortest Paths
  • 14.1.
  • Single-Source Shortest Paths
  • 14.2.
  • Dijkstra's Algorithm
  • 14.3.
  • The Bellman-Ford Algorithm
  • 14.4.
  • Shortest Paths in Directed Acyclic Graphs
  • 14.5.
  • Basic Data Structures
  • All-Pairs Shortest Paths
  • 14.6.
  • Exercises
  • 15.
  • Minimum Spanning Trees
  • 15.1.
  • Properties of Minimum Spanning Trees
  • 15.2.
  • Kruskal's Algorithm
  • 15.3.
  • 2.1.
  • The Prim-Jarnfk Algorithm
  • 15.4.
  • Baruvka's Algorithm
  • 15.5.
  • Exercises
  • 16.
  • Network Flow and Matching
  • 16.1.
  • Flows and Cuts
  • 16.2.
  • Machine generated contents note:
  • Stacks and Queues
  • Maximum Flow Algorithms
  • 16.3.
  • Maximum Bipartite Matching
  • 16.4.
  • Baseball Elimination
  • 16.5.
  • Minimum-Cost Flow
  • 16.6.
  • Exercises
  • pt. V
  • 2.2.
  • Computational Intractability
  • 17.
  • NP-Completeness
  • 17.1.
  • P and NP
  • 17.2.
  • NP-Completeness
  • 17.3.
  • CNF-SAT and 3SAT
  • 17.4.
  • Lists
  • VERTEX-COVER, CLIQUE, and SET-COVER
  • 17.5.
  • SUBSET-SUM and KNAPSACK
  • 17.6.
  • HAMILTONIAN-CYCLE and TSP
  • 17.7.
  • Exercises
  • 18.
  • Approximation Algorithms
  • 18.1.
  • 2.3.
  • The Metric Traveling Salesperson Problem
  • 18.2.
  • Approximations for Covering Problems
  • 18.3.
  • Polynomial-Time Approximation Schemes
  • 18.4.
  • Backtracking and Branch-and-Bound
  • 18.5.
  • Exercises
  • pt. VI
  • Trees
  • Additional Topics
  • 19.
  • Randomized Algorithms
  • 19.1.
  • Generating Random Permutations
  • 19.2.
  • Stable Marriages and Coupon Collecting
  • 19.3.
  • Minimum Cuts
  • 19.4.
  • 2.4.
  • Finding Prime Numbers
  • 19.5.
  • Chernoff Bounds
  • 19.6.
  • Skip Lists
  • 19.7.
  • Exercises
  • 20.
  • B-Trees and External Memory
  • 20.1.
  • Exercises
  • External Memory
  • 20.2.
  • (2,4) Trees and B-Trees
  • 20.3.
  • External-Memory Sorting
  • 20.4.
  • Online Caching Algorithms
  • 20.5.
  • Exercises
  • 21.
  • 3.
  • Multidimensional Searching
  • 21.1.
  • Range Trees
  • 21.2.
  • Priority Search Trees
  • 21.3.
  • Quadtrees and k-d Trees
  • 21.4.
  • Exercises
  • 22.
  • Binary Search Trees
  • Computational Geometry
  • 22.1.
  • Operations on Geometric Objects
  • 22.2.
  • Convex Hulls
  • 22.3.
  • Segment Intersection
  • 22.4.
  • Finding a Closest Pair of Points
  • 22.5.
  • 3.1.
  • Exercises
  • 23.
  • String Algorithms
  • 23.1.
  • String Operations
  • 23.2.
  • The Boyer-Moore Algorithm
  • 23.3.
  • The Knuth-Morris-Pratt Algorithm
  • 23.4.
  • 1.
  • Searches and Updates
  • Hash-Based Lexicon Matching
  • 23.5.
  • Tries
  • 23.6.
  • Exercises
  • 24.
  • Cryptography
  • 24.1.
  • Greatest Common Divisors (GCD)
  • 24.2.
  • 3.2.
  • Modular Arithmetic
  • 24.3.
  • Cryptographic Operations
  • 24.4.
  • The RSA Cryptosystem
  • 24.5.
  • The El Gamal Cryptosystem
  • 24.6.
  • Exercises
  • 25.
  • Range Queries
  • The Fast Fourier Transform
  • 25.1.
  • Convolution
  • 25.2.
  • Primitive Roots of Unity
  • 25.3.
  • The Discrete Fourier Transform
  • 25.4.
  • The Fast Fourier Transform Algorithm
  • 25.5.
  • 3.3.
  • Exercises
  • 26.
  • Linear Programming
  • 26.1.
  • Formulating the Problem
  • 26.2.
  • The Simplex Method
  • 26.3.
  • Duality
  • 26.4.
  • Index-Based Searching
  • Applications of Linear Programming
  • 26.5.
  • Exercises
  • 3.4.
  • Randomly Constructed Search Trees
  • 3.5.
  • Exercises
  • 4.
  • Algorithm Analysis
  • Balanced Binary Search Trees
  • 4.1.
  • Ranks and Rotations
  • 4.2.
  • AVL Trees
  • 4.3.
  • Red-Black Trees
  • 4.4.
  • Weak AVL Trees
  • 4.5.
  • 1.1.
  • Splay Trees
  • 4.6.
  • Exercises
  • 5.
  • Priority Queues and Heaps
  • 5.1.
  • Priority Queues
  • 5.2.
  • PQ-Sort, Selection-Sort, and Insertion-Sort
  • 5.3.
  • Analyzing Algorithms
  • Heaps
  • 5.4.
  • Heap-Sort
  • 5.5.
  • Extending Priority Queues
  • 5.6.
  • Exercises
  • 6.
  • Hash Tables
  • 6.1.
  • 1.2.
  • Maps
  • 6.2.
  • Hash Functions
  • 6.3.
  • Handling Collisions and Rehashing
  • 6.4.
  • Cuckoo Hashing
  • 6.5.
  • Universal Hashing
  • 6.6.
  • A Quick Mathematical Review
  • Exercises
  • 7.
  • Union-Find Structures
  • 7.1.
  • Union-Find and Its Applications
  • 7.2.
  • A List-Based Implementation
  • 7.3.
  • A Tree-Based Implementation
  • 7.4.
  • 1.3.
  • Exercises
  • pt. II
  • Sorting and Selection
  • 8.
  • Merge-Sort and Quick-Sort
  • 8.1.
  • Merge-Sort
  • 8.2.
  • Quick-Sort
  • 8.3.
Control code
ocn875249233
Dimensions
20 cm
Extent
784 pages :
Isbn
9781118335918
Isbn Type
(hardback)
Lccn
2014021534
Media category
unmediated
Media MARC source
rdamedia
System control number
(OCoLC)875249233
Label
Algorithm design and applications, Michael T. Goodrich, Department of Information and Computer Science, University of California, Irvine, Roberto Tamassia, Department of Computer Science, Brown University
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
Contents
  • A Case Study in Algorithm Analysis
  • A Lower Bound on Comparison-Based Sorting
  • 8.4.
  • Exercises
  • 9.
  • Fast Sorting and Selection
  • 9.1.
  • Bucket-Sort and Radix-Sort
  • 9.2.
  • Selection
  • 9.3.
  • 1.4.
  • Weighted Medians
  • 9.4.
  • Exercises
  • pt. III
  • Fundamental Techniques
  • 10.
  • The Greedy Method
  • 10.1.
  • The Fractional Knapsack Problem
  • 10.2.
  • Amortization
  • Task Scheduling
  • 10.3.
  • Text Compression and Huffman Coding
  • 10.4.
  • Exercises
  • 11.
  • Divide-and-Conquer
  • 11.1.
  • Recurrences and the Master Theorem
  • 11.2.
  • 1.5.
  • Integer Multiplication
  • 11.3.
  • Matrix Multiplication
  • 11.4.
  • The Maxima-Set Problem
  • 11.5.
  • Exercises
  • 12.
  • Dynamic Programming
  • 12.1.
  • Exercises
  • Matrix Chain-Products
  • 12.2.
  • The General Technique
  • 12.3.
  • Telescope Scheduling
  • 12.4.
  • Game Strategies
  • 12.5.
  • The Longest Common Subsequence Problem
  • 12.6.
  • pt. I
  • The 0-1 Knapsack Problem
  • 12.7.
  • Exercises
  • 13.
  • Graphs and Traversals
  • 13.1.
  • Graph Terminology and Representations
  • 13.2.
  • Depth-First Search
  • 13.3.
  • Data Structures
  • Breadth-First Search
  • 13.4.
  • Directed Graphs
  • 13.5.
  • Biconnected Components
  • 13.6.
  • Exercises
  • pt. IV
  • Graph Algorithms
  • 14.
  • 2.
  • Shortest Paths
  • 14.1.
  • Single-Source Shortest Paths
  • 14.2.
  • Dijkstra's Algorithm
  • 14.3.
  • The Bellman-Ford Algorithm
  • 14.4.
  • Shortest Paths in Directed Acyclic Graphs
  • 14.5.
  • Basic Data Structures
  • All-Pairs Shortest Paths
  • 14.6.
  • Exercises
  • 15.
  • Minimum Spanning Trees
  • 15.1.
  • Properties of Minimum Spanning Trees
  • 15.2.
  • Kruskal's Algorithm
  • 15.3.
  • 2.1.
  • The Prim-Jarnfk Algorithm
  • 15.4.
  • Baruvka's Algorithm
  • 15.5.
  • Exercises
  • 16.
  • Network Flow and Matching
  • 16.1.
  • Flows and Cuts
  • 16.2.
  • Machine generated contents note:
  • Stacks and Queues
  • Maximum Flow Algorithms
  • 16.3.
  • Maximum Bipartite Matching
  • 16.4.
  • Baseball Elimination
  • 16.5.
  • Minimum-Cost Flow
  • 16.6.
  • Exercises
  • pt. V
  • 2.2.
  • Computational Intractability
  • 17.
  • NP-Completeness
  • 17.1.
  • P and NP
  • 17.2.
  • NP-Completeness
  • 17.3.
  • CNF-SAT and 3SAT
  • 17.4.
  • Lists
  • VERTEX-COVER, CLIQUE, and SET-COVER
  • 17.5.
  • SUBSET-SUM and KNAPSACK
  • 17.6.
  • HAMILTONIAN-CYCLE and TSP
  • 17.7.
  • Exercises
  • 18.
  • Approximation Algorithms
  • 18.1.
  • 2.3.
  • The Metric Traveling Salesperson Problem
  • 18.2.
  • Approximations for Covering Problems
  • 18.3.
  • Polynomial-Time Approximation Schemes
  • 18.4.
  • Backtracking and Branch-and-Bound
  • 18.5.
  • Exercises
  • pt. VI
  • Trees
  • Additional Topics
  • 19.
  • Randomized Algorithms
  • 19.1.
  • Generating Random Permutations
  • 19.2.
  • Stable Marriages and Coupon Collecting
  • 19.3.
  • Minimum Cuts
  • 19.4.
  • 2.4.
  • Finding Prime Numbers
  • 19.5.
  • Chernoff Bounds
  • 19.6.
  • Skip Lists
  • 19.7.
  • Exercises
  • 20.
  • B-Trees and External Memory
  • 20.1.
  • Exercises
  • External Memory
  • 20.2.
  • (2,4) Trees and B-Trees
  • 20.3.
  • External-Memory Sorting
  • 20.4.
  • Online Caching Algorithms
  • 20.5.
  • Exercises
  • 21.
  • 3.
  • Multidimensional Searching
  • 21.1.
  • Range Trees
  • 21.2.
  • Priority Search Trees
  • 21.3.
  • Quadtrees and k-d Trees
  • 21.4.
  • Exercises
  • 22.
  • Binary Search Trees
  • Computational Geometry
  • 22.1.
  • Operations on Geometric Objects
  • 22.2.
  • Convex Hulls
  • 22.3.
  • Segment Intersection
  • 22.4.
  • Finding a Closest Pair of Points
  • 22.5.
  • 3.1.
  • Exercises
  • 23.
  • String Algorithms
  • 23.1.
  • String Operations
  • 23.2.
  • The Boyer-Moore Algorithm
  • 23.3.
  • The Knuth-Morris-Pratt Algorithm
  • 23.4.
  • 1.
  • Searches and Updates
  • Hash-Based Lexicon Matching
  • 23.5.
  • Tries
  • 23.6.
  • Exercises
  • 24.
  • Cryptography
  • 24.1.
  • Greatest Common Divisors (GCD)
  • 24.2.
  • 3.2.
  • Modular Arithmetic
  • 24.3.
  • Cryptographic Operations
  • 24.4.
  • The RSA Cryptosystem
  • 24.5.
  • The El Gamal Cryptosystem
  • 24.6.
  • Exercises
  • 25.
  • Range Queries
  • The Fast Fourier Transform
  • 25.1.
  • Convolution
  • 25.2.
  • Primitive Roots of Unity
  • 25.3.
  • The Discrete Fourier Transform
  • 25.4.
  • The Fast Fourier Transform Algorithm
  • 25.5.
  • 3.3.
  • Exercises
  • 26.
  • Linear Programming
  • 26.1.
  • Formulating the Problem
  • 26.2.
  • The Simplex Method
  • 26.3.
  • Duality
  • 26.4.
  • Index-Based Searching
  • Applications of Linear Programming
  • 26.5.
  • Exercises
  • 3.4.
  • Randomly Constructed Search Trees
  • 3.5.
  • Exercises
  • 4.
  • Algorithm Analysis
  • Balanced Binary Search Trees
  • 4.1.
  • Ranks and Rotations
  • 4.2.
  • AVL Trees
  • 4.3.
  • Red-Black Trees
  • 4.4.
  • Weak AVL Trees
  • 4.5.
  • 1.1.
  • Splay Trees
  • 4.6.
  • Exercises
  • 5.
  • Priority Queues and Heaps
  • 5.1.
  • Priority Queues
  • 5.2.
  • PQ-Sort, Selection-Sort, and Insertion-Sort
  • 5.3.
  • Analyzing Algorithms
  • Heaps
  • 5.4.
  • Heap-Sort
  • 5.5.
  • Extending Priority Queues
  • 5.6.
  • Exercises
  • 6.
  • Hash Tables
  • 6.1.
  • 1.2.
  • Maps
  • 6.2.
  • Hash Functions
  • 6.3.
  • Handling Collisions and Rehashing
  • 6.4.
  • Cuckoo Hashing
  • 6.5.
  • Universal Hashing
  • 6.6.
  • A Quick Mathematical Review
  • Exercises
  • 7.
  • Union-Find Structures
  • 7.1.
  • Union-Find and Its Applications
  • 7.2.
  • A List-Based Implementation
  • 7.3.
  • A Tree-Based Implementation
  • 7.4.
  • 1.3.
  • Exercises
  • pt. II
  • Sorting and Selection
  • 8.
  • Merge-Sort and Quick-Sort
  • 8.1.
  • Merge-Sort
  • 8.2.
  • Quick-Sort
  • 8.3.
Control code
ocn875249233
Dimensions
20 cm
Extent
784 pages :
Isbn
9781118335918
Isbn Type
(hardback)
Lccn
2014021534
Media category
unmediated
Media MARC source
rdamedia
System control number
(OCoLC)875249233

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