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 Roughgarden, Tim, author.
 First edition.  San Francisco, CA : Soundlikeyourself Publishing LLC, [2018]
 Description
 Book — xi, 209 pages : illustrations ; 23 cm
 Online
Engineering Library (Terman)
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On reserve: Ask at circulation desk  
QA76.9 .A43 R682 2017 PT.2  Unknown 2hour loan 
CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad
 Roughgarden, Tim, author.
 San Francisco, CA : Soundlikeyourself Publishing LLC, [2017]
 Description
 Book — xii, 204 pages : illustrations ; 23 cm
 Summary

"Algorithms are the heart and soul of computer science. Their applications range from network routing and computational genomics to publickey cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subjecta transcript of what an expert algorithms tutor would say over a series of oneonone lessons. Part 1 covers asymptotic analysis and bigO notation, divideandconquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection."Back cover.
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Engineering Library (Terman)
Engineering Library (Terman)  Status 

On reserve: Ask at circulation desk  
QA76.9 .A43 R68 2017  Unknown 2hour loan 
CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad
3. Introduction to algorithms [2009]
 3rd ed.  Cambridge, Mass. : MIT Press, c2009.
 Description
 Book — xix, 1292 p. : ill. ; 24 cm.
 Summary

NOTE: This International Student Edition is not available in the USA or Canada. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively selfcontained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, and substantial additions to the chapter on recurrences (now called "DivideandConquer"). It features improved treatment of dynamic programming and greedy algorithms and a new notion of edgebased flow in the material on flow networks. Many new exercises and problems have been added for this edition. As of the third edition, this textbook is published exclusively by the MIT Press.
(source: Nielsen Book Data)9780262533058 20160528
 Online
Engineering Library (Terman)
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On reserve: Ask at circulation desk  
QA76.6 .I5858 2009  Unknown 2hour loan 
CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad
 3rd ed.  Cambridge, Mass. : MIT Press, 2009.
 Description
 Book — xix, 1292 p. : ill.
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CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad
5. Algorithms [2008]
 Dasgupta, Sanjoy.
 Boston : McGrawHill Higher Education, ©2008. 
 Description
 Book — x, 320 pages : illustrations ; 24 cm
 Summary

 0 Prologue1 Algorithms with Numbers2 DivideandConquer Algorithms3 Decompositions of Graphs4 Paths in Graphs5 Greedy algorithms6 Dynamic Programming7 Linear Programming and Reductions8 NPcomplete Problems9 Coping with NPcompleteness10 Quantum Algorithms.
 (source: Nielsen Book Data)9780073523408 20180924
(source: Nielsen Book Data)9780073523408 20180924
 Online
Engineering Library (Terman)
Engineering Library (Terman)  Status 

On reserve: Ask at circulation desk  
QA9.58 .D37 2008  Unknown 2hour loan 
CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad
6. Algorithm design [2006]
 Kleinberg, Jon.
 Boston : Pearson/AddisonWesley, c2006.
 Description
 Book — xxiii, 838 p. : ill. ; 24 cm.
 Summary

 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 BreadthFirst 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 UnionFind Data Structure 4.7 Clustering 4.8 Huffman Codes and the Problem of Data Compression *4.9 MinimumCost Arborescences: A MultiPhase 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 SubProblems 6.3 Segmented Least Squares: Multiway 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 FordFulkerson Algorithm 7.2 Maximum Flows and Minimum Cuts in a Network 7.3 Choosing Good Augmenting Paths *7.4 The PreflowPush 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 PolynomialTime Reductions 8.2 Reductions via "Gadgets": The Satisfiability Problem 8.3 Efficient Certification and the Definition of NP 8.4 NPComplete Problems 8.5 Sequencing Problems 8.6 Partitioning Problems 8.7 Graph Coloring 8.8 Numerical Problems 8.9 CoNP 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 PSPACEComplete Solved Exercises Exercises Notes and Further Reading 10 Extending the Limits of Tractability 10.1 Finding Small Vertex Covers 10.2 Solving NPHard 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 BestResponse 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 3SAT 13.5 Randomized DivideandConquer: MedianFinding 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
 Online
Engineering Library (Terman)
Engineering Library (Terman)  Status 

On reserve: Ask at circulation desk  
QA76.9 .A43 K54 2006  Unknown 2hour loan 
QA76.9 .A43 K54 2006  Unknown 2hour loan 
CS16101
 Course
 CS16101  Design and Analysis of Algorithms
 Instructor(s)
 Rubinstein, Aviad