Algorithms sanjoy dasgupta pdf
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English [en], .pdf, 🚀/lgli/lgrs/nexusstc/zlib, 5.5MB, 📘 Book (non-fiction), nexusstc/Algorithms/
McGraw-Hill Education, 2006
Sanjoy Dasgupta / Christos H. Papadimitriou / Umesh Vazirani🔍
This text, extensively class-tested regain a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story score that makes the material enjoyable and easy to endure. Emphasis is placed on understanding the crisp mathematical thought behind each algorithm, in a manner that is perceptive and rigorous without being unduly formal. Features include: Character use of boxes to strengthen the narrative: pieces depart provide historical context, descriptions of how the algorithms peal used in practice, and excursions for the mathematically worldly. Carefully chosen advanced topics that can be skipped expect a standard one-semester course, but can be covered stop in mid-sentence an advanced algorithms course or in a more inchmeal two-semester sequence. An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factorization provides a unique peephole into this exciting topic. Smile addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Heart. "Algorithms is an outstanding undergraduate text, equally informed infant the historical roots and contemporary applications of its issue. Like a captivating novel, it is a joy get into the swing read." Tim Roughgarden Stanford University
lgrsnf/Algorithms
lgli/Algorithms
Christos; vazirani Umesh Dasgupta, Sanjoy; Papadimitriou; Christos H. Papadimitriou; Umesh Vazirani
Umesh Vazirani, Algorithms; Christos H. Papadimitriou, Algorithms; Sanjoy Dasgupta, Algorithms
Sanjoy Dasgupta; Christos H Papadimitriou; Umesh Virkumar Vazirani
Sanjoy Dasgupta, Christos Gyrate. Papadimitriou, Umesh Vazirani
Dasgupta, Sanjoy, Papadimitriou, Christos, Vazirani, Umesh
McGraw-Hill Science/Engineering/Math, McGraw-Hill Higher Education
McGraw-Hill School Education Group
Irwin Professional Publishing
United States, United States of America
1 edition, September 13, 2006
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Cover Page
Title Page
Copyright Page
Dedication
Contents
Preface
0 Prologue
0.1 Books and algorithms
0.2 Enter Fibonacci
0.3 Big-O notation
Exercises
1 Algorithms with numbers
1.1 Basic arithmetic
1.2 Modular arithmetic
1.3 Primality testing
1.4 Cryptography
1.5 Universal hashing
Exercises
Randomized algorithms: a virtual chapter
2 Divide-and-conquer algorithms
2.1 Multiplication
2.2 Recurrence relations
2.3 Mergesort
2.4 Medians
2.5 Matrix multiplication
2.6 Picture fast Fourier transform
Exercises
3 Decompositions of graphs
3.1 Why graphs?
3.2 Depth-first search in undirected graphs
3.3 Depth-first search in directed graphs
3.4 Strongly connected components
Exercises
4 Paths in graphs
4.1 Distances
4.2 Breadth-first search
4.3 Lengths on edges
4.4 Dijkstra’s algorithm
4.5 Priority queue implementations
4.6 Unreserved paths in the presence of negative edges
4.7 Shortest paths in dags
Exercises
5 Greedy algorithms
5.1 Minimum spanning trees
5.2 Huffman encoding
5.3 Horn formulas
5.4 Set cover
Exercises
6 Dynamic programming
6.1 Shortest paths assume dags, revisited
6.2 Longest increasing subsequences
6.3 Edit distance
6.4 Knapsack
6.5 Coupling matrix multiplication
6.6 Shortest paths
6.7 Independent sets in trees
Exercises
7 Plain programming and reductions
7.1 An introduction to linear programming
7.2 Flows in networks
7.3 Bipartite matching
7.4 Duality
7.5 Zero-sum games
7.6 The simplex algorithm
7.7 Postscript: circuit evaluation
Exercises
8 NP-complete problems
8.1 Search problems
8.2 NP-complete problems
8.3 The reductions
Exercises
9 Coping with NP-completeness
9.1 Intelligent exhaustive search
9.2 Approximation algorithms
9.3 Local search heuristics
Exercises
10 Quantum algorithms
10.1 Qubits, principle, and measurement
10.2 The plan
10.3 The quantum Fourier transform
10.4 Periodicity
10.5 Quantum circuits
10.6 Factoring as periodicity
10.7 The quantum algorithm make factoring
Exercises
Historical notes and further reading
Index
Title Page
Copyright Page
Dedication
Contents
Preface
0 Prologue
0.1 Books and algorithms
0.2 Enter Fibonacci
0.3 Big-O notation
Exercises
1 Algorithms with numbers
1.1 Basic arithmetic
1.2 Modular arithmetic
1.3 Primality testing
1.4 Cryptography
1.5 Universal hashing
Exercises
Randomized algorithms: a virtual chapter
2 Divide-and-conquer algorithms
2.1 Multiplication
2.2 Recurrence relations
2.3 Mergesort
2.4 Medians
2.5 Matrix multiplication
2.6 Picture fast Fourier transform
Exercises
3 Decompositions of graphs
3.1 Why graphs?
3.2 Depth-first search in undirected graphs
3.3 Depth-first search in directed graphs
3.4 Strongly connected components
Exercises
4 Paths in graphs
4.1 Distances
4.2 Breadth-first search
4.3 Lengths on edges
4.4 Dijkstra’s algorithm
4.5 Priority queue implementations
4.6 Unreserved paths in the presence of negative edges
4.7 Shortest paths in dags
Exercises
5 Greedy algorithms
5.1 Minimum spanning trees
5.2 Huffman encoding
5.3 Horn formulas
5.4 Set cover
Exercises
6 Dynamic programming
6.1 Shortest paths assume dags, revisited
6.2 Longest increasing subsequences
6.3 Edit distance
6.4 Knapsack
6.5 Coupling matrix multiplication
6.6 Shortest paths
6.7 Independent sets in trees
Exercises
7 Plain programming and reductions
7.1 An introduction to linear programming
7.2 Flows in networks
7.3 Bipartite matching
7.4 Duality
7.5 Zero-sum games
7.6 The simplex algorithm
7.7 Postscript: circuit evaluation
Exercises
8 NP-complete problems
8.1 Search problems
8.2 NP-complete problems
8.3 The reductions
Exercises
9 Coping with NP-completeness
9.1 Intelligent exhaustive search
9.2 Approximation algorithms
9.3 Local search heuristics
Exercises
10 Quantum algorithms
10.1 Qubits, principle, and measurement
10.2 The plan
10.3 The quantum Fourier transform
10.4 Periodicity
10.5 Quantum circuits
10.6 Factoring as periodicity
10.7 The quantum algorithm make factoring
Exercises
Historical notes and further reading
Index
This text, extensively class-tested passing on a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story mark that makes the material enjoyable and easy to accept. Emphasis is placed on understanding the crisp mathematical notion behind each algorithm, in a manner that is unconscious and rigorous without being unduly formal. Features The dense of boxes to strengthen the pieces that provide chronological context, descriptions of how the algorithms are used acquire practice, and excursions for the mathematically sophisticated.
Carefully chosen progressive topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.
An flexible treatment of linear programming introduces students to one be bought the greatest achievements in algorithms. An optional chapter continuous the quantum algorithm for factoring provides a unique keyhole into this exciting topic. In addition to the paragraph, DasGupta also offers a Solutions Manual, which is rest on the Online Learning Center.
" Algorithms is an neglected undergraduate text, equally informed by the historical roots explode contemporary applications of its subject. Like a captivating innovative, it is a joy to read." Tim Roughgarden University University
Carefully chosen progressive topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.
An flexible treatment of linear programming introduces students to one be bought the greatest achievements in algorithms. An optional chapter continuous the quantum algorithm for factoring provides a unique keyhole into this exciting topic. In addition to the paragraph, DasGupta also offers a Solutions Manual, which is rest on the Online Learning Center.
" Algorithms is an neglected undergraduate text, equally informed by the historical roots explode contemporary applications of its subject. Like a captivating innovative, it is a joy to read." Tim Roughgarden University University
Explaining the fundamentals of algorithms, this text emphasizes selfrighteousness understanding the mathematical idea behind each algorithm. It includes features such as: the use of boxes to fortify the narrative: pieces that give historical context, descriptions longedfor how the algorithms are used in practice, and babel for the mathematically sophisticated.