1. Graph theory [2010]
- Book
- xviii, 436 p. : ill. ; 24 cm.
- The Basics.- Matching Covering and Packing.- Connectivity.- Planar Graphs.- Colouring.- Flows.- Extremal Graph Theory.- Infinite Graphs.- Ramsey Theory for Graphs.- Hamilton Cycles.- Random Graphs.- Minors Trees and WQO.
- (source: Nielsen Book Data)9783642142789 20160604
(source: Nielsen Book Data)9783642142789 20160604
- The Basics.- Matching Covering and Packing.- Connectivity.- Planar Graphs.- Colouring.- Flows.- Extremal Graph Theory.- Infinite Graphs.- Ramsey Theory for Graphs.- Hamilton Cycles.- Random Graphs.- Minors Trees and WQO.
- (source: Nielsen Book Data)9783642142789 20160604
(source: Nielsen Book Data)9783642142789 20160604
Engineering Library (Terman)
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA166 .D51413 2010 | Unknown 3-day loan |
CME-305-01, MS&E-316-01
- Course
- CME-305-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
- Course
- MS&E-316-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
2. Algorithmic game theory [2007]
- Book
- xxi, 754 p. : ill. ; 26 cm.
- Introduction Noam Nisan, Tim Roughgarden, Eva Tardos and Vijay V. Vazirani-- Part I. Computing in Games: 1. Basic solution concepts and computational issues Eva Tardos and Vijay V. Vazirani-- 2. Algorithms for equilibria Christos Papadimitriou-- 3. Equilibrium computation for games in strategic and extensive form Bernhard von Stengel-- 4. Learning, regret minimization and correlated equilibria Avrim Blum and Yishay Mansour-- 5. Graphical games Michael J. Kearns-- 6. Cryptography and game theory Yevgeniy Dodis and Tal Rabin-- 7. Combinatorial algorithms for market equilibria Vijay V. Vazirani-- 8. Computation of market equilibria by convex programming Bruno Codenotti and Kasturi Varadarajan-- Part II. Algorithmic Mechanism Design: 9. Introduction to mechanism design (for computer scientists) Noam Nisan-- 10. Mechanism design without money James Schummer and Rakesh V. Vohra-- 11. Combinatorial auctions Noam Nisan and Liad Blumrosen-- 12. Computationally efficient approximation mechanisms Ron Lavi-- 13. Profit maximization in mechanism design Jason Hartline and Anna Karlin-- 14. Distributed algorithmic mechanism design Joan Feigenbaum, Michael Schapira and Scott Shenker-- 15. Cost sharing Kamal Jain and Mohammad Mahdian-- 16. On-line mechanisms David C. Parkes-- Part III. Quantifying the Inefficiency of Equilibria: 17. Introduction to the inefficiency of equilibria Tim Roughgarden and Eva Tardos-- 18. Routing games Tim Roughgarden-- 19. Inefficiency of equilibria in network formation games Eva Tardos and Tom Wexler-- 20. Selfish load-balancing Berthold Vocking-- 21. Efficiency loss and the design of scalable resource allocation mechanisms Ramesh Johari-- Part IV. Additional Topics: 22. Incentives and pricing in communication networks Asuman Ozdaglar and R. Srikant-- 23. Incentives in peer-to-peer systems John Chuang, Michal Feldman and Moshe Babaioff-- 24. Cascading behavior in networks: algorithmic and economic issues Jon Kleinberg-- 25. Incentives and information security Ross Anderson, Tyler Moore, Shishir Nagaraja and Andy Ozment-- 26. Computational aspects of information markets David M. Pennock and Rahul Sami-- 27. Manipulation-resistant reputation systems Eric Friedman, Paul Resnick and Rahul Sami-- 28. Sponsored search auctions Sebastien Lahaie, David M. Pennock, Amin Saberi and Rakesh V. Vohra-- 29. Algorithmic issues in evolutionary game theory Michael Kearns and Siddharth Suri.
- (source: Nielsen Book Data)9780521872829 20160528
(source: Nielsen Book Data)9780521872829 20160528
- Introduction Noam Nisan, Tim Roughgarden, Eva Tardos and Vijay V. Vazirani-- Part I. Computing in Games: 1. Basic solution concepts and computational issues Eva Tardos and Vijay V. Vazirani-- 2. Algorithms for equilibria Christos Papadimitriou-- 3. Equilibrium computation for games in strategic and extensive form Bernhard von Stengel-- 4. Learning, regret minimization and correlated equilibria Avrim Blum and Yishay Mansour-- 5. Graphical games Michael J. Kearns-- 6. Cryptography and game theory Yevgeniy Dodis and Tal Rabin-- 7. Combinatorial algorithms for market equilibria Vijay V. Vazirani-- 8. Computation of market equilibria by convex programming Bruno Codenotti and Kasturi Varadarajan-- Part II. Algorithmic Mechanism Design: 9. Introduction to mechanism design (for computer scientists) Noam Nisan-- 10. Mechanism design without money James Schummer and Rakesh V. Vohra-- 11. Combinatorial auctions Noam Nisan and Liad Blumrosen-- 12. Computationally efficient approximation mechanisms Ron Lavi-- 13. Profit maximization in mechanism design Jason Hartline and Anna Karlin-- 14. Distributed algorithmic mechanism design Joan Feigenbaum, Michael Schapira and Scott Shenker-- 15. Cost sharing Kamal Jain and Mohammad Mahdian-- 16. On-line mechanisms David C. Parkes-- Part III. Quantifying the Inefficiency of Equilibria: 17. Introduction to the inefficiency of equilibria Tim Roughgarden and Eva Tardos-- 18. Routing games Tim Roughgarden-- 19. Inefficiency of equilibria in network formation games Eva Tardos and Tom Wexler-- 20. Selfish load-balancing Berthold Vocking-- 21. Efficiency loss and the design of scalable resource allocation mechanisms Ramesh Johari-- Part IV. Additional Topics: 22. Incentives and pricing in communication networks Asuman Ozdaglar and R. Srikant-- 23. Incentives in peer-to-peer systems John Chuang, Michal Feldman and Moshe Babaioff-- 24. Cascading behavior in networks: algorithmic and economic issues Jon Kleinberg-- 25. Incentives and information security Ross Anderson, Tyler Moore, Shishir Nagaraja and Andy Ozment-- 26. Computational aspects of information markets David M. Pennock and Rahul Sami-- 27. Manipulation-resistant reputation systems Eric Friedman, Paul Resnick and Rahul Sami-- 28. Sponsored search auctions Sebastien Lahaie, David M. Pennock, Amin Saberi and Rakesh V. Vohra-- 29. Algorithmic issues in evolutionary game theory Michael Kearns and Siddharth Suri.
- (source: Nielsen Book Data)9780521872829 20160528
(source: Nielsen Book Data)9780521872829 20160528
site.ebrary.com ebrary
Engineering Library (Terman), eReserve
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA269 .A43 2007 | Unknown 3-day loan |
eReserve | Status |
---|---|
Instructor's copy | |
(no call number) | Unknown 2-hour loan |
CME-305-01, MS&E-316-01
- Course
- CME-305-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
- Course
- MS&E-316-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
3. Algorithm design [2006]
- Book
- xxiii, 838 p. : ill. ; 24 cm.
- Algorithm Design Jon Kleinberg and Eva Tardos Table of Contents 1 Introduction: Some Representative Problems 1.1 A First Problem: Stable Matching 1.2 Five Representative Problems Solved Exercises Excercises Notes and Further Reading 2 Basics of Algorithms Analysis 2.1 Computational Tractability 2.2 Asymptotic Order of Growth Notation 2.3 Implementing the Stable Matching Algorithm using Lists and Arrays 2.4 A Survey of Common Running Times 2.5 A More Complex Data Structure: Priority Queues Solved Exercises Exercises Notes and Further Reading 3 Graphs 3.1 Basic Definitions and Applications 3.2 Graph Connectivity and Graph Traversal 3.3 Implementing Graph Traversal using Queues and Stacks 3.4 Testing Bipartiteness: An Application of Breadth-First Search 3.5 Connectivity in Directed Graphs 3.6 Directed Acyclic Graphs and Topological Ordering Solved Exercises Exercises Notes and Further Reading 4 Greedy Algorithms 4.1 Interval Scheduling: The Greedy Algorithm Stays Ahead 4.2 Scheduling to Minimize Lateness: An Exchange Argument 4.3 Optimal Caching: A More Complex Exchange Argument 4.4 Shortest Paths in a Graph 4.5 The Minimum Spanning Tree Problem 4.6 Implementing Kruskal's Algorithm: The Union-Find Data Structure 4.7 Clustering 4.8 Huffman Codes and the Problem of Data Compression *4.9 Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm Solved Exercises Excercises Notes and Further Reading 5 Divide and Conquer 5.1 A First Recurrence: The Mergesort Algorithm 5.2 Further Recurrence Relations 5.3 Counting Inversions 5.4 Finding the Closest Pair of Points 5.5 Integer Multiplication 5.6 Convolutions and The Fast Fourier Transform Solved Exercises Exercises Notes and Further Reading 6 Dynamic Programming 6.1 Weighted Interval Scheduling: A Recursive Procedure 6.2 Weighted Interval Scheduling: Iterating over Sub-Problems 6.3 Segmented Least Squares: Multi-way Choices 6.4 Subset Sums and Knapsacks: Adding a Variable 6.5 RNA Secondary Structure: Dynamic Programming Over Intervals 6.6 Sequence Alignment 6.7 Sequence Alignment in Linear Space 6.8 Shortest Paths in a Graph 6.9 Shortest Paths and Distance Vector Protocols *6.10 Negative Cycles in a Graph Solved Exercises Exercises Notes and Further Reading 7 Network Flow 7.1 The Maximum Flow Problem and the Ford-Fulkerson Algorithm 7.2 Maximum Flows and Minimum Cuts in a Network 7.3 Choosing Good Augmenting Paths *7.4 The Preflow-Push Maximum Flow Algorithm 7.5 A First Application: The Bipartite Matching Problem 7.6 Disjoint Paths in Directed and Undirected Graphs 7.7 Extensions to the Maximum Flow Problem 7.8 Survey Design 7.9 Airline Scheduling 7.10 Image Segmentation 7.11 Project Selection 7.12 Baseball Elimination *7.13 A Further Direction: Adding Costs to the Matching Problem Solved Exercises Exercises Notes and Further Reading 8 NP and Computational Intractability 8.1 Polynomial-Time Reductions 8.2 Reductions via "Gadgets": The Satisfiability Problem 8.3 Efficient Certification and the Definition of NP 8.4 NP-Complete Problems 8.5 Sequencing Problems 8.6 Partitioning Problems 8.7 Graph Coloring 8.8 Numerical Problems 8.9 Co-NP and the Asymmetry of NP 8.10 A Partial Taxonomy of Hard Problems Solved Exercises Exercises Notes and Further Reading 9 PSPACE: A Class of Problems Beyond NP 9.1 PSPACE 9.2 Some Hard Problems in PSPACE 9.3 Solving Quantified Problems and Games in Polynomial Space 9.4 Solving the Planning Problem in Polynomial Space 9.5 Proving Problems PSPACE-Complete Solved Exercises Exercises Notes and Further Reading 10 Extending the Limits of Tractability 10.1 Finding Small Vertex Covers 10.2 Solving NP-Hard Problem on Trees 10.3 Coloring a Set of Circular Arcs *10.4 Tree Decompositions of Graphs *10.5 Constructing a Tree Decomposition Solved Exercises Exercises Notes and Further Reading 11 Approximation Algorithms 11.1 Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem 11.2 The Center Selection Problem 11.3 Set Cover: A General Greedy Heuristic 11.4 The Pricing Method: Vertex Cover 11.5 Maximization via the Pricing method: The Disjoint Paths Problem 11.6 Linear Programming and Rounding: An Application to Vertex Cover *11.7 Load Balancing Revisited: A More Advanced LP Application 11.8 Arbitrarily Good Approximations: the Knapsack Problem Solved Exercises Exercises Notes and Further Reading 12 Local Search 12.1 The Landscape of an Optimization Problem 12.2 The Metropolis Algorithm and Simulated Annealing 12.3 An Application of Local Search to Hopfield Neural Networks 12.4 Maximum Cut Approximation via Local Search 12.5 Choosing a Neighbor Relation *12.6 Classification via Local Search 12.7 Best-Response Dynamics and Nash Equilibria Solved Exercises Exercises Notes and Further Reading 13 Randomized Algorithms 13.1 A First Application: Contention Resolution 13.2 Finding the Global Minimum Cut 13.3 Random Variables and their Expectations 13.4 A Randomized Approximation Algorithm for MAX 3-SAT 13.5 Randomized Divide-and-Conquer: Median-Finding and Quicksort 13.6 Hashing: A Randomized Implementation of Dictionaries 13.7 Finding the Closest Pair of Points: A Randomized Approach 13.8 Randomized Caching 13.9 Chernoff Bounds 13.10 Load Balancing *13.11 Packet Routing 13.12 Background: Some Basic Probability Definitions Solved Exercises Exercises Notes and Further Reading Epilogue: Algorithms that Run Forever References Index.
- (source: Nielsen Book Data)9780321295354 20160528
(source: Nielsen Book Data)9780321295354 20160528
- Algorithm Design Jon Kleinberg and Eva Tardos Table of Contents 1 Introduction: Some Representative Problems 1.1 A First Problem: Stable Matching 1.2 Five Representative Problems Solved Exercises Excercises Notes and Further Reading 2 Basics of Algorithms Analysis 2.1 Computational Tractability 2.2 Asymptotic Order of Growth Notation 2.3 Implementing the Stable Matching Algorithm using Lists and Arrays 2.4 A Survey of Common Running Times 2.5 A More Complex Data Structure: Priority Queues Solved Exercises Exercises Notes and Further Reading 3 Graphs 3.1 Basic Definitions and Applications 3.2 Graph Connectivity and Graph Traversal 3.3 Implementing Graph Traversal using Queues and Stacks 3.4 Testing Bipartiteness: An Application of Breadth-First Search 3.5 Connectivity in Directed Graphs 3.6 Directed Acyclic Graphs and Topological Ordering Solved Exercises Exercises Notes and Further Reading 4 Greedy Algorithms 4.1 Interval Scheduling: The Greedy Algorithm Stays Ahead 4.2 Scheduling to Minimize Lateness: An Exchange Argument 4.3 Optimal Caching: A More Complex Exchange Argument 4.4 Shortest Paths in a Graph 4.5 The Minimum Spanning Tree Problem 4.6 Implementing Kruskal's Algorithm: The Union-Find Data Structure 4.7 Clustering 4.8 Huffman Codes and the Problem of Data Compression *4.9 Minimum-Cost Arborescences: A Multi-Phase Greedy Algorithm Solved Exercises Excercises Notes and Further Reading 5 Divide and Conquer 5.1 A First Recurrence: The Mergesort Algorithm 5.2 Further Recurrence Relations 5.3 Counting Inversions 5.4 Finding the Closest Pair of Points 5.5 Integer Multiplication 5.6 Convolutions and The Fast Fourier Transform Solved Exercises Exercises Notes and Further Reading 6 Dynamic Programming 6.1 Weighted Interval Scheduling: A Recursive Procedure 6.2 Weighted Interval Scheduling: Iterating over Sub-Problems 6.3 Segmented Least Squares: Multi-way Choices 6.4 Subset Sums and Knapsacks: Adding a Variable 6.5 RNA Secondary Structure: Dynamic Programming Over Intervals 6.6 Sequence Alignment 6.7 Sequence Alignment in Linear Space 6.8 Shortest Paths in a Graph 6.9 Shortest Paths and Distance Vector Protocols *6.10 Negative Cycles in a Graph Solved Exercises Exercises Notes and Further Reading 7 Network Flow 7.1 The Maximum Flow Problem and the Ford-Fulkerson Algorithm 7.2 Maximum Flows and Minimum Cuts in a Network 7.3 Choosing Good Augmenting Paths *7.4 The Preflow-Push Maximum Flow Algorithm 7.5 A First Application: The Bipartite Matching Problem 7.6 Disjoint Paths in Directed and Undirected Graphs 7.7 Extensions to the Maximum Flow Problem 7.8 Survey Design 7.9 Airline Scheduling 7.10 Image Segmentation 7.11 Project Selection 7.12 Baseball Elimination *7.13 A Further Direction: Adding Costs to the Matching Problem Solved Exercises Exercises Notes and Further Reading 8 NP and Computational Intractability 8.1 Polynomial-Time Reductions 8.2 Reductions via "Gadgets": The Satisfiability Problem 8.3 Efficient Certification and the Definition of NP 8.4 NP-Complete Problems 8.5 Sequencing Problems 8.6 Partitioning Problems 8.7 Graph Coloring 8.8 Numerical Problems 8.9 Co-NP and the Asymmetry of NP 8.10 A Partial Taxonomy of Hard Problems Solved Exercises Exercises Notes and Further Reading 9 PSPACE: A Class of Problems Beyond NP 9.1 PSPACE 9.2 Some Hard Problems in PSPACE 9.3 Solving Quantified Problems and Games in Polynomial Space 9.4 Solving the Planning Problem in Polynomial Space 9.5 Proving Problems PSPACE-Complete Solved Exercises Exercises Notes and Further Reading 10 Extending the Limits of Tractability 10.1 Finding Small Vertex Covers 10.2 Solving NP-Hard Problem on Trees 10.3 Coloring a Set of Circular Arcs *10.4 Tree Decompositions of Graphs *10.5 Constructing a Tree Decomposition Solved Exercises Exercises Notes and Further Reading 11 Approximation Algorithms 11.1 Greedy Algorithms and Bounds on the Optimum: A Load Balancing Problem 11.2 The Center Selection Problem 11.3 Set Cover: A General Greedy Heuristic 11.4 The Pricing Method: Vertex Cover 11.5 Maximization via the Pricing method: The Disjoint Paths Problem 11.6 Linear Programming and Rounding: An Application to Vertex Cover *11.7 Load Balancing Revisited: A More Advanced LP Application 11.8 Arbitrarily Good Approximations: the Knapsack Problem Solved Exercises Exercises Notes and Further Reading 12 Local Search 12.1 The Landscape of an Optimization Problem 12.2 The Metropolis Algorithm and Simulated Annealing 12.3 An Application of Local Search to Hopfield Neural Networks 12.4 Maximum Cut Approximation via Local Search 12.5 Choosing a Neighbor Relation *12.6 Classification via Local Search 12.7 Best-Response Dynamics and Nash Equilibria Solved Exercises Exercises Notes and Further Reading 13 Randomized Algorithms 13.1 A First Application: Contention Resolution 13.2 Finding the Global Minimum Cut 13.3 Random Variables and their Expectations 13.4 A Randomized Approximation Algorithm for MAX 3-SAT 13.5 Randomized Divide-and-Conquer: Median-Finding and Quicksort 13.6 Hashing: A Randomized Implementation of Dictionaries 13.7 Finding the Closest Pair of Points: A Randomized Approach 13.8 Randomized Caching 13.9 Chernoff Bounds 13.10 Load Balancing *13.11 Packet Routing 13.12 Background: Some Basic Probability Definitions Solved Exercises Exercises Notes and Further Reading Epilogue: Algorithms that Run Forever References Index.
- (source: Nielsen Book Data)9780321295354 20160528
(source: Nielsen Book Data)9780321295354 20160528
Engineering Library (Terman)
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA76.9 .A43 K54 2006 | Unknown 2-hour loan |
QA76.9 .A43 K54 2006 | Unknown 2-hour loan |
CME-305-01, MS&E-316-01
- Course
- CME-305-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
- Course
- MS&E-316-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
4. Randomized algorithms [1995]
- Book
- 476 p.
- Part I. Tools and Techniques: 1. Introduction-- 2. Game-theoretic techniques-- 3. Moments and deviations-- 4. Tail inequalities-- 5. The probabilistic method-- 6. Markov chains and random walks-- 7. Algebraic techniques-- Part II. Applications: 8. Data structures-- 9. Geometric algorithms and linear programming-- 10. Graph algorithms-- 11. Approximate counting-- 12. Parallel and distributed algorithms-- 13. Online algorithms-- 14. Number theory and algebra-- Appendix A: notational index-- Appendix B: mathematical background-- Appendix C: basic probability theory.
- (source: Nielsen Book Data)9780521474658 20160528
(source: Nielsen Book Data)9780521474658 20160528
- Part I. Tools and Techniques: 1. Introduction-- 2. Game-theoretic techniques-- 3. Moments and deviations-- 4. Tail inequalities-- 5. The probabilistic method-- 6. Markov chains and random walks-- 7. Algebraic techniques-- Part II. Applications: 8. Data structures-- 9. Geometric algorithms and linear programming-- 10. Graph algorithms-- 11. Approximate counting-- 12. Parallel and distributed algorithms-- 13. Online algorithms-- 14. Number theory and algebra-- Appendix A: notational index-- Appendix B: mathematical background-- Appendix C: basic probability theory.
- (source: Nielsen Book Data)9780521474658 20160528
(source: Nielsen Book Data)9780521474658 20160528
Engineering Library (Terman), eReserve
Engineering Library (Terman) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA274 .M68 1995 | Unknown 3-day loan |
QA274 .M68 1995 | Unknown 3-day loan |
eReserve | Status |
---|---|
Instructor's copy | |
INTERNET ACCESS | Unknown 2-hour loan |
CME-305-01, MS&E-316-01
- Course
- CME-305-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh
- Course
- MS&E-316-01 -- Discrete Mathematics and Algorithms
- Instructor(s)
- Bosagh, Reza Zadeh