1. Algorithms [2022]
 Mueller, John, 1958 author.
 2nd edition.  Hoboken, NJ : John Wiley & Sons, Inc., [2022]
 Description
 Book — 1 online resource (448 pages).
 Summary

Your secret weapon to understandingand using!one of the most powerful influences in the world today From your Facebook News Feed to your most recent insurance premiumseven making toast!algorithms play a role in virtually everything that happens in modern society and in your personal life. And while they can seem complicated from a distance, the reality is that, with a little help, anyone can understandand even usethese powerful problemsolving tools! In Algorithms For Dummies, you'll discover the basics of algorithms, including what they are, how they work, where you can find them (spoiler alert: everywhere!), who invented the most important ones in use today (a Greek philosopher is involved), and how to create them yourself. You'll also find: Dozens of graphs and charts that help you understand the inner workings of algorithms Links to an online repository called GitHub for constant access to updated code Stepbystep instructions on how to use Google Colaboratory, a zerosetup coding environment that runs right from your browser Whether you're a curious internet user wondering how Google seems to always know the right answer to your question or a beginning computer science student looking for a head start on your next class, Algorithms For Dummies is the can'tmiss resource you've been waiting for.
 Feng, Oliver Y., author.
 Norwell, MA : Now Publishers, 2022
 Description
 Book — 1 online resource Sound: digital.
 Summary

 1. Introduction
 2. Master Theorems for Abstract AMP Recursions
 3. LowRank Matrix Estimation
 4. GAMP for Generalised Linear Models
 5. Conclusions and Extensions Acknowledgements Appendices References.
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(source: Nielsen Book Data)
 Online

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Business Library
Business Library  Status 

Online resource  
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3. Algorithmic barriers falling : P=NP? [2014]
 Knuth, Donald Ervin, 1938 interviewee.
 Belgium : Lonely Scholar Scientific Books, [2014]
 Description
 Book — xix, 116 pages ; 23 cm.
 Online
4. Practical analysis of algorithms [2014]
 Vrajitoru, Dana, author.
 Cham : Springer, 2014.
 Description
 Book — 1 online resource (xii, 466 pages) : illustrations Digital: text file.PDF.
 Summary

 Introduction Mathematical Preliminaries Fundamental Notations in Analysis of Algorithms Recurrence Relations Deterministic Analysis of Algorithms Algorithms and Probabilities Finite Graph Algorithms Appendix: Probability Theory.
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(source: Nielsen Book Data)
5. Algorithms unlocked [2013]
 Cormen, Thomas H., author.
 Cambridge, Massachusetts : MIT Press, c2013 [Piscataqay, New Jersey] : IEEE Xplore, [2013]
 Description
 Book — 1 online resource (xiii, 222 pages) : illustrations
 Summary

Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone? This book offers an engagingly written guide to the basics of computer algorithms. In Algorithms Unlocked, Thomas Cormen  coauthor of the leading college textbook on the subject  provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them. They will discover simple ways to search for information in a computer; methods for rearranging information in a computer into a prescribed order ("sorting"); how to solve basic problems that can be modeled in a computer with a mathematical structure called a "graph" (useful for modeling road networks, dependencies among tasks, and financial relationships); how to solve problems that ask questions about strings of characters such as DNA structures; the basic principles behind cryptography; fundamentals of data compression; and even that there are some problems that no one has figured out how to solve on a computer in a reasonable amount of time.
(source: Nielsen Book Data)
 Sedgewick, Robert, 1946
 2nd ed.  Upper Saddle River, NJ : AddisonWesley, 2013.
 Description
 Book — xvii, 572 p. : ill. ; 24 cm
 Summary

 Chapter 1: Analysis of Algorithms 3 1.1 Why Analyze an Algorithm? 3 1.2 Theory of Algorithms 6 1.3 Analysis of Algorithms 13 1.4 AverageCase Analysis 16 1.5 Example: Analysis of Quicksort 18 1.6 Asymptotic Approximations 27 1.7 Distributions 30 1.8 Randomized Algorithms 33
 Chapter 2: Recurrence Relations 41 2.1 Basic Properties 43 2.2 FirstOrder Recurrences 48 2.3 Nonlinear FirstOrder Recurrences 52 2.4 HigherOrder Recurrences 55 2.5 Methods for Solving Recurrences 61 2.6 Binary DivideandConquer Recurrences and Binary Numbers 70 2.7 General DivideandConquer Recurrences 80
 Chapter 3: Generating Functions 91 3.1 Ordinary Generating Functions 92 3.2 Exponential Generating Functions 97 3.3 Generating Function Solution of Recurrences 101 3.4 Expanding Generating Functions 111 3.5 Transformations with Generating Functions 114 3.6 Functional Equations on Generating Functions 117 3.7 Solving the Quicksort MedianofThree Recurrence with OGFs 120 3.8 Counting with Generating Functions 123 3.9 Probability Generating Functions 129 3.10 Bivariate Generating Functions 132 3.11 Special Functions 140
 Chapter 4: Asymptotic Approximations 151 4.1 Notation for Asymptotic Approximations 153 4.2 Asymptotic Expansions 160 4.3 Manipulating Asymptotic Expansions 169 4.4 Asymptotic Approximations of Finite Sums 176 4.5 EulerMaclaurin Summation 179 4.6 Bivariate Asymptotics 187 4.7 Laplace Method 203 4.8 "Normal" Examples from the Analysis of Algorithms 207 4.9 "Poisson" Examples from the Analysis of Algorithms 211
 Chapter 5: Analytic Combinatorics 219 5.1 Formal Basis 220 5.2 Symbolic Method for Unlabelled Classes 221 5.3 Symbolic Method for Labelled Classes 229 5.4 Symbolic Method for Parameters 241 5.5 Generating Function Coefficient Asymptotics 247
 Chapter 6: Trees 257 6.1 Binary Trees 258 6.2 Forests and Trees 261 6.3 Combinatorial Equivalences to Trees and Binary Trees 264 6.4 Properties of Trees 272 6.5 Examples of Tree Algorithms 277 6.6 Binary Search Trees 281 6.7 Average Path Length in Catalan Trees 287 6.8 Path Length in Binary Search Trees 293 6.9 Additive Parameters of Random Trees 297 6.10 Height 302 6.11 Summary of AverageCase Results on Properties of Trees 310 6.12 Lagrange Inversion 312 6.13 Rooted Unordered Trees 315 6.14 Labelled Trees 327 6.15 Other Types of Trees 331
 Chapter 7: Permutations 345 7.1 Basic Properties of Permutations 347 7.2 Algorithms on Permutations 355 7.3 Representations of Permutations 358 7.4 Enumeration Problems 366 7.5 Analyzing Properties of Permutations with CGFs 372 7.6 Inversions and Insertion Sorts 384 7.7 LefttoRight Minima and Selection Sort 393 7.8 Cycles and In Situ Permutation 401 7.9 Extremal Parameters 406
 Chapter 8: Strings and Tries 415 8.1 String Searching 416 8.2 Combinatorial Properties of Bitstrings 420 8.3 Regular Expressions 432 8.4 FiniteState Automata and the KnuthMorrisPratt Algorithm 437 8.5 ContextFree Grammars 441 8.6 Tries 448 8.7 Trie Algorithms 453 8.8 Combinatorial Properties of Tries 459 8.9 Larger Alphabets 465
 Chapter 9: Words and Mappings 473 9.1 Hashing with Separate Chaining 474 9.2 The BallsandUrns Model and Properties of Words 476 9.3 Birthday Paradox and Coupon Collector Problem 485 9.4 Occupancy Restrictions and Extremal Parameters 495 9.5 Occupancy Distributions 501 9.6 Open Addressing Hashing 509 9.7 Mappings 519 9.8 Integer Factorization and Mappings 532 List of Theorems 543 List of Tables 545 List of Figures 547 Index 551.
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Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
QA76.9 .A43 S43 2013  Unknown 
7. Algorithmes [2011]
 Knuth, Donald Ervin, 1938 author.
 Stanford, California : CSLI Publications, [2011]
 Description
 Book — xiv, 510 pages : illustrations ; 24 cm.
 Summary

 L'informatique et ses rapports avec les mathématiques
 Mathématiques et informatique : faire face au fini
 Les algorithmes
 Les problèmes récréatifs sontils utiles?
 Analyse mathématique des algorithmes
 Les dangers de l'informatique théorique
 L'analyse des algorithmes
 Notes sur le contournement des instructions 'goto'
 Programmation structurée avec des instructions goto (1974)
 Les liens valsants
 Analyse syntaxique descendante
 Sur la traduction des langages de gauche à droite
 Sémantique des langages algébriques
 Sondage linéaire et graphes
 Recherche rapide de motifs dans les textes
 Problèmes de mots simples dans les algèbres universelles
 Permutations, matrices et tableaux de Young généralisés.
 Online
Green Library
Green Library  Status 

Find it Jonsson Social Sciences Reading Room: CSLI publications  
P51 .C18 NO.194  Unknown 
Find it Stacks  
P51 .C18 NO.194  Unknown 
 Bisbal Riera, Jesús, author.
 Primera edición en lengua castellana.  Barcelona : Universitat Oberta de Catalunya, 2009.
 Description
 Book — 1 online resource (235 pages).
9. Advanced data structures [2008]
 Brass, Peter.
 Cambridge, UK ; New York : Cambridge University Press, 2008.
 Description
 Book — xvi, 456 p. : ill. ; 24 cm.
 Summary

 1. Elementary structures
 2. Search types
 3. Balanced search trees
 4. Tree structures for sets of intervals
 5. Heaps
 6. Unionfind and related structures
 7. Data structure transformations
 8. Data structures for strings
 9. Hash tables
 10. Appendix.
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Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks  
QA76.9 .A43 B73 2008  Unknown 
 Brass, Peter.
 Cambridge ; New York : Cambrige University Press, 2008.
 Description
 Book — xvi, 456 p. : ill.
11. Algorithms in a nutshell [2008]
 Heineman, George T.
 1st ed.  Beijing ; Sebastopol, Calif. : O'Reilly, c2008.
 Description
 Book — xv, 343 p. : ill. ; 23 cm.
 Summary

Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. "Algorithms in a Nutshell" describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs  with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate.With this book, you will: solve a particular coding problem or improve on the performance of an existing solution; quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use; get algorithmic solutions in C, C++, Java, and Ruby with implementation tips; learn the expected performance of an algorithm, and the conditions it needs to perform at its best; discover the impact that similar design decisions have on different algorithms; and, learn advanced data structures to improve the efficiency of algorithms. With "Algorithms in a Nutshell", you'll learn how to improve the performance of key algorithms essential for the success of your software applications.
(source: Nielsen Book Data)
Science Library (Li and Ma)
Science Library (Li and Ma)  Status 

Stacks  
QA76.9 .A43 H45 2008  Unknown 
 Hoboken, N.J. : WileyInterscience, c2008.
 Description
 Book — 1 online resource (xxvi, 544 p.) : ill.
 Summary

 Preface. Abstracts. Contributors.
 1. Generating All and Random Instances of A combinatorial Object (Ivan Stojmenovic)
 2. Backtracking and IsomorphFree Generation of Polyhexes (Lucia Moura and Ivan Stojmenovic)
 3. Graph Theoretic Models in Chemistry and Molecular Biology (Debra Knisley and Jeff Knisley)
 4. Algorithmic Methods for the Analysis of Gene Expression Data (Hongbo Xie, Uros Midic, Slobodan Vucetic, and Zoran Obradovic)
 5. Algorithms of ReactionDiffusion Computing (Andrew Adamatzky)
 6. Data Mining Algorithms I: Clustering (Dan A. Simovici)
 7. Data Mining Algorithms II: Frequent Item Sets (Dan A. Simovici)
 8. Algorithms for Data Streams (Camil Demetrescu and Irene Finocchi)
 9. Applying Evolutionary Algorithms to Solve the Automatic Frequency Planning Problem (Francisco Luna, Enrique Alba, Antonio J. Nero, Patrick Nauru, and Salvador Pedraza)
 10. Algorithmic Game Theory and Application s(Marios Mavronicolas, Vicky Papdopoulou, and Paul Spirakis)
 11. Algorithms for RealTime Object Detection in Images (Milos Stojmenovic)
 12. 2D Shape Measures for Computer Vision (Paul L. Rosin and Jovisa Zunic)
 13. Cryptographic Algorithms (Binal Roy and Amiya Nayak)
 14. Secure Communication in Distributed Sensor Networks (DSN) (Subhamoy Maitra and Bimal Roy)
 15. Localized Topology Control Algorithms for Ad Hoc and Sensor Networks (Hannes Frey and David SimplotRyl)
 16. A Novel Admission Control for Multimedia LEO Satellite Networks (Syed R. Rizvi, Stephan Olariu, and Mona E. Rizvi)
 17. Resilient Recursive Routing in Communication Networks (Costas C. Constantinou, Alexander S. Stepanenko, Theodoros N. Arvanitis, Kevin J. Baughan, and Bin Liu)
 18. Routing Algorithms on WDM Optical Networks (QianPing Gu) Index.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Kuhn, D. Richard.
 [Gaithersburg, MD] : U.S. Dept. of Commerce, National Institute of Standards and Technology, [2006]
 Description
 Book — 1 online resource (4 unnumbered pages).
 Szpankowski, Wojciech, 1952
 New York : John Wiley, c2001.
 Description
 Book — xxii, 551 p. : ill. ; 25 cm.
 Summary

 Foreword. Preface. Acknowledgments. PROBLEMS ON WORDS. Data Structures and Algorithms on Words. Probabilistic and Analytical Models. PROBABILISTIC AND COMBINATORIAL TECHNIQUES. InclusionExclusion Principle. The First and Second Moment Methods. Subadditive Ergodic Theorem and Large Deviations. Elements of Information Theory. ANALYTIC TECHNIQUES. Generating Functions. Complex Asymptotic Methods. Mellin Transform and Its Applications. Analytic Poissonization and Depoissonization. Bibliography. Index.
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(source: Nielsen Book Data)
Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks  
QA76.9 .A43 S87 2001  Unknown 
 Baase, Sara.
 3rd ed.  Reading, Mass. : Addison Wesley, c2000.
 Description
 Book — xix, 688 p. : ill. ; 24 cm.
 Summary

 1. Analyzing Algorithms and Problems: Principles and Examples. Introduction. Java as an Algorithm Language. A Usable Subset of Java. Organizer Classes. JavaBased Pseudocode Conventions. Mathematical Background. Sets, Tuples, and Relations. Algebra and Calculus Tools. Elements of Logic. Analyzing Algorithms and Problems. Correctness. Amount of Work Done. Average and WorstCase Analysis. Space Usage. Simplicity. Optimality. Lower Bounds and the Complexity of Problems. Implementation and Programming. Classifying Functions by their Asymptotic Growth Rates. Definitions and Notation. How Important Is Asymptotic Order? Properties of O, Theta, and Omega. The Asymptotic Order of Commonly Occuring Sums. Searching an Ordered Array. Some Solutions. WorstCase Analysis of Binary Search. AverageBehavior Analysis. Optimality.
 2. Data Abstraction and Basic Data Structures. Introduction. ADT Specifications and Design Techniques. ADT Specifications. ADT Design Techniques. Elementary ADTs  Lists and Trees. Recursive ADTs. The List ADT. Binary Tree ADT. The Tree ADT. InTree ADT. Stacks and Queues. Stack ADT. Queue ADT. ADTs for Dynamic Sets. Priority Queue ADT. UnionFind ADT for Disjoint Sets. Dictionary ADT.
 3. Recursion and Induction. Introduction. Recursive Procedures. Activation Frames and Recursive Procedure Calls. Hints for Recursion  Method
 99. Wrappers for Recursive Procedures. What is a Proof? Induction Proofs. Induction Proof Schema. Induction Proof on a Recursive Procedure. Proving Correctness of Procedures. Definitions and Terminology. Elementary Control Structures. The SingleAssignment Paradigm. Procedures with Loops. Correctness Proofs as a Debugging Tool. Termination of Recursive Procedures. Correctness of Binary Search. Recurrence Equations. Recursion Trees. DivideandConquer, General Case. Chip and Conquer, or be Conquered. Why Recursion Trees Work (*).
 4. Sorting. Introduction. Insertion Sort. The Strategy. The Algorithm and Analysis. Lower Bounds on the Behavior of Certain Sorting Algorithms. Divide and Conquer. Quicksort. The Quicksort Strategy. The Partition Subroutine. Analysis of Quicksort. Improvements on the Basic Quicksort Algorithm. Merging Sorted Sequences. Worst Case. Optimality of Merge. Space Usage. Mergesort. Lower Bounds for Sorting by Comparison of Keys. Decision Trees for Sorting Algorithms. Lower Bound for Worst Case. Lower Bound for Average Behavior. Heapsort. Heaps. The Heapsort Strategy. FixHeap. Heap Construction. Implementation of a Heap and the Heapsort Algorithm. Accelerated Heapsort. Comparison of Four Sorting Methods. Shellsort. The Algorithm. Analysis and Remarks. Radix Sorting. Using Properties of the Keys. Radix Sort.
 5. Selection and Adversary Arguments. Introduction. The Selection Problem. Lower Bounds. Adversary Arguments. Tournaments. Finding max and min. Finding the SecondLargest Key. Introduction. The Tournament Method. An Adversary LowerBound Argument. Implementation of the Tournament Method for Finding max and secondLargest. The Selection Problem. A DivideandConquer Approach. A LinearTime Selection Algorithm (*). Analysis of the Selection Algorithm (*). A Lower Bound for Finding the Median. Designing Against an Adversary.
 6. Dynamic Sets and Searching. Introduction. Array Doubling. Amortized Time Analysis. RedBlack Trees. Binary Search Trees. Binary Tree Rotations. RedBlack Tree Definitions. Size and Depth of RedBlack Trees. Insertion into a RedBlack Tree. Deletion from a RedBlack Tree. Hashing. Closed Address Hashing. Open Address Hashing. Hash Functions. Dynamic Equivalence Relations and UnionFind Programs. Dynamic Equivalence Relations. Some Obvious Implementations. UnionFind Programs. Weighted Union. Path Compression. Analysis of wUnion and cFind (*). Applications. Priority Queues with a Decrease Key Operation. The Decrease Key Operation. Pairing Forests.
 7. Graphs and Graph Traversals. Definitions and Representations. Some Examples. Elementary Graph Definitions. Graph Representations and Data Structures. Traversing Graphs. Overview of DepthFirst Search. Overview of BreadthFirst Search. Comparison of DepthFirst and BreadthFirst Searches. DepthFirst Search and Recursion. Finding Connected Components with DepthFirst Search. DepthFirst Search Trees. A Generalized DepthFirst Search Skeleton. Structure of DepthFirst Search. Directed Acyclic Graphs and Topological Sort. Strongly Connected Components of a Directed Graph. Definitions. A Strong Component Algorithm. Analysis. Biconnected Components of an Undirected Graph. Articulation Points and Biconnected Components. The Bicomponent Algorithm. Analysis. Generalizations.
 8. Graph Optimization Problems and Greedy Algorithms. Introduction. Prim's Minimum Spanning Tree Algorithm. Definition and Examples of Minimum Spanning Trees. An Overview of the Algorithm. Properties of Minimum Spanning Trees. Correctness of Prim's MST Algorithm. Managing the Fringe Efficiently with a Priority Queue. Implementation. Analysis (Time and Space). Lower Bound. SingleSource Shortest Paths. Background. Properties of Shortest Paths. Dijkstra's ShortestPath Algorithm. Implementation. Kruskal's Minimum Spanning Tree Algorithm. Analysis.
 9. Transitive Closure, AllPairs Shortest Paths. The Transitive Closure of a Binary Relation. Definitions and Background. Finding the Reachability Matrix by DepthFirst Search. Transitive Closure by Short Cuts. Warshalls Algorithm for Transitive Closure. The Basic Algorithm. Warshalls Algorithm for Bit Matrices. Distances in Graphs. Computing Transitive Closure by Matrix Operations. Multiplying Bit Matrices  Kronrod's Algorithm. Introduction. Kronrods Algorithm. Lower Bound (*).
 10. Dynamic Programming. Introduction. Multiplying a Sequence of Matrices. Constructing Optimal Binary Search Trees. Separating Words into Lines. Some Comments on Developing a Dynamic Programming Algorithm.
 11. String Matching. A Straightforward Solution. The KnuthMorrisPratt Algorithm. Pattern Matching with Finite Automata. The KnuthMorrisPratt Flowchart. Construction of the KMP Flowchart. Analysis of the Flowchart Construction. The KnuthMorrisPratt Scan Algorithm. The BoyerMoore Algorithm. The New Idea. And the "Old" Idea. The BoyerMoore Scan Algorithm. Remarks. Approximate String Matching. Exercises.
 12. Polynomials and Matrices. Introductory Comments. Evaluating Polynomial Functions. Algorithms. Lower Bounds for Polynomial Evaluation. Preprocessing of Coefficients. Vector and Matrix Multiplication. Review of Standard Algorithms. Winograd's Matrix Multiplication. Lower Bounds for Matrix Multiplication. Strassen's Matrix Multiplication. The Fast Fourier Transform and Convolution (*). Introduction. The Fast Fourier Transform. Convolution. Appendix: Complex Numbers and Roots of Unity.
 13. NPComplete Problems. P and NP. Decision Problems. Some Sample Problems. The Class P. The Class NP. The Size of the Input. NPComplete Problems. Polynomial Reductions. Some Known NPComplete Problems. What Makes a Problem Hard? Optimization Problems and Decision Problems. Approximation Algorithms. Bin Packing. The First Fit Decreasing Strategy. Other Heuristics. The Knapsack and SubsetSum Problems. Graph Coloring. Some Basic Techniques. Approximate Graph Coloring Is Hard. Wigderson's Graph Coloring Algorithm. The Traveling Salesperson Problem. Greedy Strategies. The Nearest Neighbor Strategy. The Shortest Link Strategy. How Good Are the TSP Approximation Algorithms? Computing with DNA. The Problem and an Overview of the Algorithm. DNA Background. Adleman's Directed Graph and the DNA Algorithm. Analysis and Evaluation.
 14. Parallel Algorithms. Parallelism, the PRAM, and Other Models. Introduction. The PRAM. Other Models. Some PRAM Algorithms. The Binary FanIn Technique. Some Easily Parallelizable Algorithms. Handling Write Conflicts. Boolean or on n Bits. An Algorithm for Finding Maximum in Constant Time. Merging and Sorting. Introduction. Merging. Sorting. Finding Connected Components. Strategy and Techniques. The Algorithm. PRAM Implementation of the Algorithm. Analysis. A Lower Bound for Computing a Function on n Bits. A: Java Examples and Techniques. A Java "Main Program." Library IntListLib Examples. Generic Order and the "Comparable" Interface. Copy via the "Clone" Interface. Subclasses Extend the Capability of Their Superclass. 0201612445T04062001.
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Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks  
QA76.6 .B25 2000  Unknown 
 ALENEX '99 (1999 : Baltimore, Md.)
 Berlin ; New York : Springer, c1999.
 Description
 Book — viii, 347 p. : ill. ; 24 cm.
 Summary

This book constitutes the thoroughly refereed postworkshop proceedings of the International Workshop on Algorithmic Engineering and Experimentation, ALENEX'99, held in Baltimore, Maryland, USA, in January 1999.The 20 revised full papers presented were carefully selected from a total of 42 submissions during two rounds of reviewing and improvement. The papers are organized in sections on combinatorial algorithms, computational geometry, software and applications, algorithms for NPhard problems, and data structures.
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SAL3 (offcampus storage)
SAL3 (offcampus storage)  Status 

Stacks  Request (opens in new tab) 
QA76.9 .A43 A42 1999  Available 
17. The algorithm design manual [1998]
 Skiena, Steven S.
 New York : Springer ; Santa Clara, CA : TELOS, c1998.
 Description
 Book — xvi, 486 p. : ill. ; 25 cm. + 1 computer laser optical disc (4 3/4 in.)
 Summary

 Part I: Techniques 1) Introduction to Algorithms
 2) Data Structures and Sorting
 3) Breaking Problems Down
 4) Graph Algorithms
 5) Combinatorial Search and Heuristic Methods
 6) Intractable Problems and Approximations
 7) How to Design Algorithms Part II: Resources 8) A Catalog of Algorithmic Problems
 9) Algorithmic Resources.
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Engineering Library (Terman)
Engineering Library (Terman)  Status 

Stacks


QA76.9 .A43 S55 1998  Unknown 
 Sedgewick, Robert, 1946
 Reading, Mass. : AddisonWesley, c1996.
 Description
 Book — xv, 492 p. : ill. ; 25 cm.
 Summary

 1. Analysis of Algorithms. Why Analyze an Algorithm? Computational Complexity. Analysis of Algorithms. AverageCase Analysis. Example: Analysis of Quicksort. Asymptotic Approximations. Distributions. Probabilistic Algorithms.
 2. Recurrence Relations. Basic Properties. FirstOrder Recurrences. Nonlinear FirstOrder Recurrences. HigherOrder Recurrences. Methods for Solving Recurrences. Binary DivideandConquer Recurrences and Binary Numbers. General DivideandConquer Recurrences.
 3. Generating Functions. Ordinary Generating Functions. Exponential Generating Functions. Generating Function Solution of Recurrences. Expanding Generating Functions. Transformations with Generating Functions. Functional Equations on Generating Functions. Solving the Quicksort MedianofThree. Recurrence with OGFs. Counting with Generating Functions. The Symbolic Method. Lagrange Inversion. Probability Generating Functions. Bivariate Generating Functions. Special Functions.
 4. Asymptotic Approximations. Notation for Asymptotic Approximations. Asymptotic Expansions. Manipulating Asymptotic Expansions. Asymptotic Approximations of Finite Sums. EulerMaclaurin Summation. Bivariate Asymptotics. Laplace Method. "Normal" Examples from the Analysis of Algorithms. "Poisson" Examples from the Analysis of Algorithms. Generating Function Asymptotics.
 5. Trees. Binary Trees. Trees and Forests. Properties of Trees. Tree Algorithms. Binary Search Trees. Average Path Length in Catalan Trees. Path Length in Binary Search Trees. Additive Parameters of Random Trees. Height. Summary of AverageCase Results on Properties of Trees. Representations of Trees and Binary Trees. Unordered Trees. Labelled Trees. Other Types of Trees.
 6. Permutations. Basic Properties of Permutations. Algorithms on Permutations. Representations of Permutations. Enumeration Problems. Analyzing Properties of Permutations with CGFs. Inversions and Insertion Sorts. LefttoRight Minima and Selection Sort. Cycles and In Situ Permutation. Extremal Parameters.
 7. Strings and Tries. String Searching. Combinatorial Properties of Bitstrings. Regular Expressions. FiniteState Automata and KnuthMorrisPratt Algorithm. ContextFree Grammars. Tries. Trie Algorithms. Combinatorial Properties of Tries. Larger alphabets.
 8. Words and Maps. Hashing with Separate Chaining. Basic Properties of Words. Birthday Paradox and Coupon Collector Problem. Occupancy Restrictions and Extremal Parameters. Occupancy Distributions. Open Addressing Hashing. Maps. Integer Factorization and Maps. 020140009XT04062001.
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Science Library (Li and Ma)
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Stacks  
QA76.9 .A43 S43 1996  Unknown 
 Hofri, Micha.
 New York : Oxford University Press, 1995.
 Description
 Book — 618 p.
 Summary

 Introduction. Part I: Tools of the Trade.
 1: Generating functions.
 2: Combinatorial Calculus.
 3: Representations of Permutations.
 4: Integral Transforms.
 5: Asymptotic Methods.
 6: Selected Results from Probability Theory. Part II: Trade Samples.
 7: Searching and Sorting.
 8: Algorithms for Communications Networks.
 9: Bin Packing Heuristics. Appendix A: Binomial Coefficients. Appendix B: Stirling Numbers. Appendix C: Inequalities. Appendix D: Common Random Variables. Appendix E: Linear First Order Equations. Appendix F: Complex Analysis Definitions and Theorems. Bibliography. Notation Index and Numerical Constants. Index.
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(source: Nielsen Book Data)
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SAL3 (offcampus storage)
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QA76.9.A43 H63 1995  Available 
 Los Alamitos, Calif. : IEEE Computer Society Press, c1994.
 Description
 Book — ix, 281 p. : ill. ; 29 cm.
 Summary

 Preface. CHAPTER 1: SINGLE KEYWORD MATCHING. Fast Pattern Matching in Strings (D.E. Knuth, J.H. Morris, and V.R. Pratt from SIAM Journal of Computing, June 1977). A Fast String Searching Algorithm (R.S. Boyer and J.S. Moore from Communications of the ACM, October 1977). Algorithms for Pattern Matching (G. Davies and S. Bowsher from Software
 Practice and Experience, June 1986). CHAPTER 2: MATCHING SETS OF KEYWORDS. Efficient String Matching: An Aid to Bibliographic Search (A.V. Aho and M.J. Corasick from Communications of the ACM, June 1975). A Method for Improving String Pattern Matching Machines (J. Aoe, Y. Yamamoto, and R. Shimada from IEEE Trans. on Software Engineering, January 1984). An Efficient Algorithm for Matching Multiple Patterns (J.J. Fan and K.Y. Su from IEEE Trans. on Knowledge and Data Engineering, April 1993). CHAPTER 3: APPROXIMATE STRING MATCHING. Approximate String Matching (P.V. Hall and G.R. Dowling from ACM Computing Surveys, December 1980). Optimal Correspondence of String Subsequences (Y.P. Wang and T. Pavlidis from IEEE Trans. on Pattern Analysis and Machine Intelligence, Nov. 1990). The Noisy Substring Matching Problem (R.L. Kashyap and B.J. Oommen from IEEE Trans. on Software Engineering, May 1983). CHAPTER 4: MULTIDIMENSIONAL MATCHING. Pattern Matching in Trees (C.M. Hoffmann and M.J. O'Donnell from Journal of the ACM, January 1982). Code Generation Using Tree Matching and Dynamic Programming (A.V. Aho, M. Ganapathi, and S.W.K. Tjiang from ACM Trans. on Programming Languages and Systems, Oct. 1989). The TreetoTree Correction Problem (K.C. Tai from Journal of the ACM, July 1979). A Technique for TwoDimensional Pattern Matching (R.F. Zhu and T. Takaoka from Communications of the ACM, September 1989). CHAPTER 5: HARDWARE MATCHING. Performance and Architectural Issues for String Matching (M.E. Isenman and D.E. Shasha from IEEE Trans. on Computers, February 1990). HYTREM
 A Hybrid TextRetrieval Machine for Large Databases (D.L. Lee and F.H. Lochovsky from IEEE Trans. on Computers, January 1990). REFERENCES. ABOUT THE AUTHOR.
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Stacks  Request (opens in new tab) 
QA76.9 .A43 C67 1994  Available 
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