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2. Design and analysis of algorithms [2013]
 Dave, Parag H.
 2nd ed.  New Dehli : Dorling Kindersley (India), ©2013.
 Description
 Book — 1 online resource (1 volume) : illustrations
 Berlin : Springer, 2010.
 Description
 Book — 1 online resource (xvi, 513 pages) : illustrations Digital: text file; PDF.
 Summary

 1. Foundations of Algorithm Engineering
 2. Modeling
 3. Selected Design Issues
 4. Analysis of Algorithms
 5. Realistic Computer Models
 6. Implementation Aspects
 7. Libraries
 8. Experiments
 9. Case Studies
 10. Challenges in Algorithm Engineering.
 IJTCSFAW (Conference) (2023 : Macau, China)
 Cham, Switzerland : Springer, 2023.
 Description
 Book — 1 online resource (xx, 296 pages) : illustrations (some color).
 Summary

 Understanding the Relationship Between Core Constraints and CoreSelecting Payment Rules in Combinatorial Auctions
 An Improved Analysis of the Greedy+Singleton Algorithm for kSubmodular Knapsack Maximization
 Generalized Sorting with Predictions Revisited
 Eliciting Truthful Reports with Partial Signals in Repeated Games
 On the NPhardness of two scheduling problems under linear constraints
 On the Matching Number of kUniform Connected Hypergraphs with Maximum Degree
 MaxMin Greedy Matching Problem: Hardness for the Adversary and Fractional Variant
 Approximate Core Allocations for Edge Cover Games
 Random Approximation Algorithms for Monotone kSubmodular Function Maximization with Size Constraints
 Additive Approximation Algorithms for Sliding Puzzle
 Differential Game Analysis for Cooperation Models in Automotive Supply Chain under LowCarbon Emission Reduction Policies
 Adaptivity Gap for Influence Maximization with Linear Threshold Model on Trees
 Physically Verifying the First Nonzero Term in a Sequence: Physical ZKPs for ABC End View and Goishi Hiroi
 Mechanism Design in Fair Sequencing
 RedBlue Rectangular Annulus Cover Problem
 Applying Johnson's Rule in Scheduling Multiple Parallel TwoStage Flowshops
 The Fair kCenter with Outliers Problem: FPT and Polynomial Approximations
 Constrained Graph Searching on Trees
 EFX Allocations Exist for Binary Valuations
 Maximize Egalitarian Welfare for Cake Cutting
 Stackelberg Strategies on Epidemic Containment Games.
 ESA (Symposium) (11th : 2003 : Budapest, Hungary)
 Berlin ; New York : Springer, ©2003.
 Description
 Book — 1 online resource (xiv, 790 pages) : illustrations Digital: text file.PDF.
 Summary

 Invited Lectures
 Sublinear Computing
 Authenticated Data Structures
 Approximation Algorithms and Network Games
 Contributed Papers: Design and Analysis Track
 I/OEfficient Structures for Orthogonal RangeMax and StabbingMax Queries
 Line System Design and a Generalized Coloring Problem
 Lagrangian Relaxation for the kMedian Problem: New Insights and Continuity Properties
 Scheduling for FlowTime with Admission Control
 On Approximating a Geometric PrizeCollecting Traveling Salesman Problem with Time Windows
 Semiclairvoyant Scheduling
 Algorithms for Graph Rigidity and Scene Analysis
 Optimal Dynamic VideoonDemand Using Adaptive Broadcasting
 Multiplayer and Multiround Auctions with Severely Bounded Communication
 Network Lifetime and Power Assignment in ad hoc Wireless Networks
 Disjoint Unit Spheres admit at Most Two Line Transversals
 An Optimal Algorithm for the MaximumDensity Segment Problem
 Estimating Dominance Norms of Multiple Data Streams
 Smoothed Motion Complexity
 Kinetic Dictionaries: How to Shoot a Moving Target
 Deterministic Rendezvous in Graphs
 Fast Integer Programming in Fixed Dimension
 Correlation Clustering
 Minimizing Disagreements on Arbitrary Weighted Graphs
 Dominating Sets and Local Treewidth
 Approximating Energy Efficient Paths in Wireless Multihop Networks
 Bandwidth Maximization in Multicasting
 Optimal Distance Labeling for Interval and CircularArc Graphs
 Improved Approximation of the Stable Marriage Problem
 Fast Algorithms for Computing the Smallest kEnclosing Disc
 The Minimum Generalized Vertex Cover Problem
 An Approximation Algorithm for MAX2SAT with Cardinality Constraint
 OnDemand Broadcasting Under Deadline
 Improved Bounds for Finger Search on a RAM
 The Voronoi Diagram of Planar Convex Objects
 Buffer Overflows of Merging Streams
 Improved Competitive Guarantees for QoS Buffering
 On Generalized Gossiping and Broadcasting
 Approximating the Achromatic Number Problem on Bipartite Graphs
 Adversary Immune Leader Election in ad hoc Radio Networks
 Universal Facility Location
 A Method for Creating NearOptimal Instances of a Certified WriteAll Algorithm
 I/OEfficient Undirected Shortest Paths
 On the Complexity of Approximating TSP with Neighborhoods and Related Problems
 A Lower Bound for Cake Cutting
 Ray Shooting and Stone Throwing
 Parameterized Tractability of EdgeDisjoint Paths on Directed Acyclic Graphs
 Binary Space Partition for Orthogonal Fat Rectangles
 Sequencing by Hybridization in Few Rounds
 Efficient Algorithms for the Ring Loading Problem with Demand Splitting
 Seventeen Lines and OneHundredandOne Points
 Jacobi Curves: Computing the Exact Topology of Arrangements of Nonsingular Algebraic Curves
 Contributed Papers: Engineering and Application Track
 Streaming Geometric Optimization Using Graphics Hardware
 An Efficient Implementation of a Quasipolynomial Algorithm for Generating Hypergraph Transversals
 Experiments on Graph Clustering Algorithms
 More Reliable Protein NMR Peak Assignment via Improved 2Interval Scheduling
 The Minimum Shift Design Problem: Theory and Practice
 Loglog Counting of Large Cardinalities
 Packing a Trunk
 Fast SmallestEnclosingBall Computation in High Dimensions
 Automated Generation of Search Tree Algorithms for Graph Modification Problems
 Boolean Operations on 3D Selective Nef Complexes: Data Structure, Algorithms, and Implementation
 Fleet Assignment with Connection Dependent Ground Times
 A Practical Minimum Spanning Tree Algorithm Using the Cycle Property
 The Fractional PrizeCollecting Steiner Tree Problem on Trees
 Algorithms and Experiments for the Webgraph
 Finding Short Integral Cycle Bases for Cyclic Timetabling
 Slack Optimization of TimingCritical Nets
 Multisampling: A New Approach to Uniform Sampling and Approximate Counting
 Multicommodity Flow Approximation Used for Exact Graph Partitioning
 A Linear Time Heuristic for the BranchDecomposition of Planar Graphs
 Geometric SpeedUp Techniques for Finding Shortest Paths in Large Sparse Graphs.
 ALENEX 2002 (2002 : San Francisco, Calif.)
 Berlin : Springer, 2002.
 Description
 Book — 1 online resource (viii, 205 pages) : illustrations Digital: text file.PDF.
 Summary

 ALENEX 2002
 On the Implementation of MSTBased Heuristics for the Steiner Problem in Graphs
 A TimeSensitive System for BlackBox Combinatorial Optimization
 A Compressed BreadthFirst Search for Satisfiability
 Using Multilevel Graphs for Timetable Information in Railway Systems
 Evaluating the Local Ratio Algorithm for Dynamic Storage Allocation
 An Experimental Study of Prefetching and Caching Algorithms for the World Wide Web
 The Treewidth of Java Programs
 Partitioning Planar Graphs with Costs and Weights
 Maintaining Dynamic Minimum Spanning Trees: An Experimental Study
 Experimental Evaluation of a New Shortest Path Algorithm
 Getting More from OutofCore Columnsort
 Topological Sweep in Degenerate Cases
 Acceleration of KMeans and Related Clustering Algorithms
 STARTree: An Efficient SelfAdjusting Index for Moving Objects
 An Improvement on Tree Selection Sort.
 ALENEX 2001 (2001 : Washington, D.C.)
 Berlin ; Heidelberg : Springer, ©2001.
 Description
 Book — 1 online resource (viii, 229 pages) : illustrations Digital: text file.PDF.
 Summary

 ALENEX'01
 Solving a "Hard" Problem to Approximate an "Easy" One: Heuristics for Maximum Matchings and Maximum Traveling Salesman Problems
 CNOP
 A Package for Constrained Network Optimization
 The Asymmetric Traveling Salesman Problem: Algorithms, Instance Generators, and Tests
 Network Tomography through EndtoEnd Measurements
 Experimental Results on Statistical Approaches to Page Replacement Policies
 Estimating Resemblance of MIDI Documents
 Experiments on Adaptive Set Intersections for Text Retrieval Systems
 PVD: A Stable Implementation for Computing Voronoi Diagrams of Polygonal Pockets
 Hierarchical Clustering of Trees: Algorithms and Experiments
 Travel Planning with SelfMade Maps
 New Algorithmic Challenges Arising in MeasurementDriven Networking Research
 A Probabilistic Spell for the Curse of Dimensionality
 Experimental Evaluation of the Height of a Random Set of Points in a dDimensional Cube
 An Empirical Study of a New Approach to Nearest Neighbor Searching
 Spectral Analysis for Data Mining
 Trade Off Between Compression and Search Times in Compact Suffix Array
 Implementation of a PTAS for Scheduling with Release Dates
 Biased Skip Lists for Highly Skewed Access Patterns.
8. Esquemas algoritmicos [2003]
 Rico, Juan Ramon.
 [Alicante, España] : Publicaciones de la Universidad de Alicante, ©2003.
 Description
 Book — 1 online resource
 Summary

 Intro
 Contenido
 1. Preliminares
 1.1 Introducción
 1.2 ¿Qué es un algoritmo?
 1.3 ¿Qué es la algoritmia?
 1.4 Notación para los programas
 1.5 Notación matemática
 2. Programación dinámica
 2.1 Introducción
 2.2 Esquema recursivo
 2.2.1 Principio de inducción general
 2.2.2 Principio de optimalidad
 2.3 Esquema iterativo
 2.3.1 Estructura indexada de datos
 2.3.2 Esquema Iterativo
 2.4 Problemas resueltos
 2.4.1 Hallar el camino mínimo en un grafo multietapa
 2.4.2 Mínima distancia de edición entre dos cadenas
 2.4.3 Secuencia mínima para calcular el producto entre matrices
 2.5 Ejercicios
 2.5.1 Inversiones
 2.5.2 Transporte de mármol
 2.5.3 Conexiones en Internet
 2.5.4 Evacuación de una isla
 2.5.5 Dónde llenar el depósito de gasolina
 2.5.6 Salir del laberinto
 2.6 Soluciones
 3 Ramificación y poda
 3.1 Introducción
 3.2 Esquema básico de resolución de problemas
 3.3 Refinamientos sobre el esquema básico
 3.3.1 Primer refinamiento
 3.3.2 Segundo refinamiento
 3.3.3 Solución subóptima
 3.4 Teoría de juegos
 3.5 Problemas resueltos
 3.5.1 El problema de la mochila discreto 0/1
 3.5.2 El Viajante de Comercio
 3.6 Ejercicios
 3.6.1 Dónde llenar el depósito de gasolina
 3.6.2 Reservas de laboratorio
 3.6.3 Puzzle
 3.6.4 Construcción de edificios
 3.6.5 Cena de empresa
 3.6.6 Viaje en autobuses
 3.7 Soluciones
 Referencias
 índice analítico.
9. Algorithms and applications : essay dedicated to Esko Ukkonen on the occasion of his 60th birthday [2010]
 Berlin : Springer, ©2010.
 Description
 Book — 1 online resource (x, 259 pages) : illustrations Digital: text file; PDF.
 Summary

 String Rearrangement Metrics: A Survey. Maximal Words in Sequence Comparisons Based on Subword Composition. Fast Intersection Algorithms for Sorted Sequences. Indexing and Searching a Mass Spectrometry Database. Extended Compact Web Graph Representations. A Parallel Algorithm for FixedLength Approximate StringMatching with kmismatches. Covering Analysis of the Greedy Algorithm for Partial Cover. From Nondeterministic Suffix Automaton to Lazy Suffix Tree. Clustering the Normalized Compression Distance for Influenza Virus Data. An Evolutionary Model of DNA Substring Distribution. Indexing a Dictionary for Subset Matching Queries. Transposition and TimeScale Invariant Geometric Music Retrieval. Unified View of Backward Backtracking in Short Read Mapping. Some Applications of String Algorithms in HumanComputer Interaction. Approximate String Matching with Reduced Alphabet. ICT4D: A Computer Science Perspective. Searching for Linear Dependencies between Heart Magnetic Resonance Images and Lipid Profiles. The Support Vector Tree.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
10. Heuristic search : theory and applications [2012]
 Waltham, MA : Morgan Kaufmann/Elsevier, ©2012.
 Description
 Book — 1 online resource
 Summary

 PART I Heuristic Search Primer Chapter 1 Introduction Chapter 2 Basic Search Algorithms Chapter 3 Dictionary Data Structures Chapter 4 Automatically Created Heuristics PART II Heuristic Search under Memory Constraints Chapter 5 LinearSpace Search Chapter 6 Memory Restricted Search Chapter 7 Symbolic Search Chapter 8 External Search
 PART III Heuristic Search under Time Constraints Chapter 9 Distributed Search Chapter 10 State Space Pruning Chapter 11 RealTime Search by Sven Koenig
 PART IV Heuristic Search Variants Chapter 12 Adversary Search Chapter 13 Constraint Search Chapter 14 Selective Search PART V Heurstic Search Applications Chapter 15 Action Planning Chapter 16 Automated System Verification Chapter 17 Vehicle Navigation Chapter 18 Computational Biology Chapter 19 Robotics by Sven Koenig.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Martins, Tiago.
 Cham, Switzerland : Springer, 2021.
 Description
 Book — 1 online resource (xv, 68 pages)
 Summary

 Introduction
 Related Work
 Architecture
 Evaluation
 Conclusions and future work.
(source: Nielsen Book Data)
 Alsuwaiyel, M. H.
 Singapore ; New Jersey : World Scientific, c1999.
 Description
 Book — 1 online resource (xix, 523 p.) : ill.
 Summary

Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) solution of the formulated problem. One can solve a problem on its own using ad hoc techniques or follow those techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions and the context appropriate for each of them. This book advocates the study of algorithm design techniques by presenting most of the useful algorithm design techniques and illustrating them through numerous examples.
(source: Nielsen Book Data)
 Jenkyns, T. A. (Tom A.)
 London ; New York : Springer, ©2013.
 Description
 Book — 1 online resource (xii, 416 pages) : illustrations Digital: data file.
 Summary

 Algorithms, Numbers and Machines. Sets, Sequences and Counting. Boolean Expressions, Logic and Proof. Searching and Sorting. Graphs and Trees. Relations: Especially on (Integer) Sequences. Sequences and Series. Generating Sequences and Subsets. Discrete Probability and Average Case Complexity. Turing Machines.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
 Berkeley, Calif. : Mathematical Sciences Publishers, Dept. of Mathematics, University of California, Berkeley
 Description
 Journal/Periodical
15. Property testing : problems and techniques [2022]
 Bhattacharyya, Arnab.
 Singapore : Springer, 2022.
 Description
 Book — 1 online resource (434 pages)
 Summary

 Chapter 1: Introduction.
 Chapter 2: Basic Techniques.
 Chapter 3: Strings.
 Chapter 4: Graphs in the Adjacency Metrix Model.
 Chapter 5: Graphs in the BoundedDegree Model.
 Chapter 6: Functions over Hypercubes.
 Chapter 7: Massively Parameterized Model.
 Chapter 8: Vectors and Matrices over the Reals.
 Chapter 9: Graphs in the Adjacency Matrix Model.
 Chapter 10: Graphs in the BoundedDegree Model.
 Chapter 11: AffineInvariant Properties of Functions.
 Chapter 12: Linear Properties of Functions.
 Chapter 13: Massively Parameterized Model.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
16. Advanced Algorithms and Data Structures [2021]
 La Rocca, Marcello.
 Shelter Island, NY : Manning Publications, [2021]
 Description
 Book — 1 online resource (735 pages)
 Summary

 1 Introducing data structures
 Part 1. Improving over basic data structures
 2 Improving priority queues: dway heaps
 3 Treaps: Using randomization to balance binary search trees
 4 Bloom filters: Reducing the memory for tracking content
 5 Disjoint sets: Sublinear time processing
 6 Trie, radix trie: Efficient string search
 7 Use case: LRU cache
 Part 2. Multidimensional queries
 8 Nearest neighbors search
 9 Kd trees: Multidimensional data indexing
 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval
 11 Applications of nearest neighbor search
 12 Clustering
 13 Parallel clustering: MapReduce and canopy clustering
 Part 3. Planar graphs and minimum crossing number
 14 An introduction to graphs: Finding paths of minimum distance
 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections
 16 Gradient descent: Optimization problems (not just) on graphs
 17 Simulated annealing: Optimization beyond local minima
 18 Genetic algorithms: Biologically inspired, fastconverging optimization
 Appendix A. A quick guide to pseudocode
 Appendix B. BigO notation
 Appendix C. Core data structures
 Appendix D. Containers as priority queues
 Appendix E. Recursion
 Appendix F. Classification problems and randomnized algorithm metrics
 Index.
17. Introduction to Search Algorithms [2019]
 Porbasas Flejoles, Rex.
 Ashland : Arcler Press, 2019.
 Description
 Book — 1 online resource (258 pages)
 Summary

 Cover; Half Title Page; Full Title Page; Copyright Page; About the Author; Table of Contents; List of Figures; List of Tables; Preface;
 Chapter 1 Fundamentals of Search Algorithms; 1.1. Introduction; 1.2. Unordered Linear Search; 1.3. Ordered Linear Search; 1.4. Chunk Search; 1.5. Binary Search; 1.6. Searching in Graphs; 1.7. Graph Grep; 1.8. Searching in Trees; 1.9. Searching in Temporal Probabilistic Object Data Model; References;
 Chapter 2 Fundamentals of Linear Search Algorithm; 2.1. Introduction; 2.2. Theory of The Linear Search Algorithm
 2.3. Modified Linear Search Technique With One Middle Component2.4. Modified Linear Search Technique With Two Middle Components; 2.5. TwoWay Linear Search; 2.6. Proof of Accuracy for TwoWay Linear Search; 2.7. Analysis And Comparison of Performance; References;
 Chapter 3 Introduction To A* Based BestFirst Search Algorithms; 3.1. Introduction; 3.2. BestFirst Heuristic Search: A*; 3.3. Classes; 3.4. A* Algorithm: An Overview; References;
 Chapter 4 A Fast Search Algorithm For A Large Fuzzy Database; 4.1. Introduction; 4.2. Previous Work on Fast Search Algorithms; 4.3. Algorithms
 4.4. Theoretical Results of Algorithms4.5. Experiment Results of Algorithms; 4.6. Comparison of Results; References;
 Chapter 5 RealTime Heuristic Search Algorithms For Video Games' Pathfinding; 5.1. Introduction; 5.2. Problem Formulation; 5.3. The Core Algorithms; 5.4. k Nearest Neighbors LRTA* (kNN LRTA*); 5.5. TimeBounded A* (TBA*); References;
 Chapter 6 RealTime IterativeDeepening BestFirst Search (RIBS); 6.1. Introduction; 6.2. RIBS: Intuition; 6.3. Properties of RIBS; 6.4. Empirical Evaluation of RIBS In Heuristic Depressions; References
 Chapter 7 Running Particle Swarm Optimization On Graphics Processing Units7.1. Introduction; 7.2. Particle Swarm Optimization; 7.3. Our GPUBased Particle Swarm Optimization Proposals; 7.4. Experimental Approaches For Algorithms; References;
 Chapter 8 Search Via Quantum Walk; 8.1. Introduction; 8.2. Quantum Walk; 8.3. Search Algorithm Via Quantum Walk; 8.4. Physical Implementation of Quantum Walk Based Search; 8.5. Quantum Walk Based Search in Nature; 8.6. Biomimetic Application in Solar Energy; References; Index
18. Algorithms : 24part lecture series [2015]
 Sedgewick, Robert, 1946 onscreen presenter.
 [Place of publication not identified] : AddisonWesley Professional, 2015.
 Description
 Video — 1 online resource (1 streaming video file (28 hr., 18 min., 30 sec.)) : digital, sound, color
 Summary

"This collection of video lectures provides a comprehensive exploration of fundamental data types, algorithms, and data structures, with an emphasis on applications and scientific performance analysis of Java implementations. The instructors offer readings related to these lectures that you can find in Algorithms, Fourth Edition, the leading textbook on algorithms today. These lectures provide another perspective on the material presented in the book and generally cover the material in the same order, though some book topics have been combined, rearranged, or omitted in the lectures."Resource description page.
 Kirk, Matthew, author.
 Sebastopol, California : O'Reilly, 2015.
 Description
 Book — 1 online resource (235 pages) : illustrations (some color)
 Summary

Learn how to apply testdriven development (TDD) to machinelearning algorithms  and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machinelearning algorithms, including Naive Bayesian classifiers and Neural Networks. Machinelearning algorithms often have tests baked in, but they can't account for human errors in coding. Rather than blindly rely on machinelearning results as many researchers have, you can mitigate the risk of errors with TDD and write clean, stable machinelearning code. If you're familiar with Ruby 2.1, you're ready to start. Apply TDD to write and run tests before you start coding Learn the best uses and tradeoffs of eight machine learning algorithms Use realworld examples to test each algorithm through engaging, handson exercises Understand the similarities between TDD and the scientific method for validating solutions Be aware of the risks of machine learning, such as underfitting and overfitting data Explore techniques for improving your machinelearning models or data extraction.
(source: Nielsen Book Data)
20. Algorithms in motion [2018]
 Carnes, Beau, onscreen presenter.
 [Place of publication not identified] : Manning Publications, 2018.
 Description
 Video — 1 online resource (1 streaming video file (4 hr., 11 min., 7 sec.)) Digital: data file.
 Summary

"Algorithms in Motion teaches you how to apply common algorithms to the practical problems you face every day as a programmer. Following the expert guidance of live video instructor Beau Carnes, you'll start with the basics, including Big O notation, fundamental data structures, and recursion. Then, you'll explore problemsolving techniques, that will empower you to see the algorithm you need in the task you're trying to accomplish. Finally, you'll finish the course by applying more advanced algorithms, such as hash tables, graph algorithms, and Knearest."Resource description page
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