Search Results - (((((((ant OR kantor) OR wiant) OR data) OR cantor) OR anne) OR halted) OR antiii) algorithms.

How to think about algorithms by Edmonds, Jeff, 1963-

Table of Contents: “…Iterative algorithms: measures of progress and loop invariants -- Examples using more-of-the-input loop invariants -- Abstract data types -- Narrowing the search space: binary search -- Iterative sorting algorithms -- Euclid's GCD algorithm -- The loop invariant for lower bounds -- Abstractions, techniques, and theory -- Some simple examples of recursive algorithms -- Recursion on trees -- Recursive images -- Parsing with context-free grammars -- Definition of optimization problems -- Graph search algorithms -- Network flows and linear programming -- Greedy algorithms -- Recursive backtracking -- Dynamic programming algorithms -- Examples of dynamic programs -- Reductions and NP-completeness -- Randomized algorithms -- Existential and universal quantifiers -- Time complexity -- Logarithms and exponentials -- Asymptotic growth -- Adding-made-easy approximations -- Recurrence relations -- A formal proof of correctness.…”
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Electronic and Algorithmic Trading Technology : the Complete Guide. by Kim, Kendall

Table of Contents: “…Front Cover; Electronic and Algorithmic Trading Technology; Copyright Page; Dedication Page; Contents; About the Author; Series Preface; Introduction; Chapter 1: Overview of Electronic and Algorithmic Trading; Chapter 2: Automating Trade and Order Flow; Chapter 3: The Growth of Program and Algorithmic Trading; Chapter 4: Alternative Execution Venues; Chapter 5: Algorithmic Strategies; Chapter 6: Algorithmic Feasibility and Limitations; Cahpter 7: Electronic Trading Networks; Chapter 8: Effective Data Management; Chapter 9: Minimizing Execution Costs; Chapter 10: Transaction Cost Research.…”
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Graph algorithms and applications 3

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Graph Algorithms and Applications 2 : Solid-Electrolyte Interphase. by Liotta, Giuseppe

Table of Contents: “…Difference Metrics for Interactive Orthogonal Graph Drawing Algorithms Techniques for the Refinement of Orthogonal Graph Drawings ; A Split & Push Approach to 3D Orthogonal Drawing ; Using Graph Layout to Visualize Train Interconnection Data.…”
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Graph algorithms and applications 4

Table of Contents: “…Special issue on selected papers from the Seventh International Workshop on Algorithms and Data Structures, WADS 2001 / Guest editor(s): Giuseppe Liotta and Ioannis G. …”
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Evolutionary computation in gene regulatory network research

Table of Contents: “…I: Preliminaries -- A Brief Introduction to Evolutionary and other Nature-Inspired Algorithms / Nasimul Noman and Hitoshi Iba -- Mathematical Models and Computational Methods for Inference of Genetic Networks / Tatsuya Akutsu -- Gene Regulatory Networks: Real Data Sources and Their Analysis / Yuji Zhang -- II: EAs for Gene Expression Data Analysis and GRN Reconstruction -- Biclustering Analysis of Gene Expression Data Using Evolutionary Algorithms / Alan Wee-Chung Liew -- Inference of Vohradský's Models of Genetic Networks Using a Real-Coded Genetic Algorithm / Shuhei Kimura -- GPU-Powered Evolutionary Design of Mass-Action-Based Models of Gene Regulation / Marco S. …”
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Analysis of biological networks

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Metaheuristic optimization for the design of automatic control laws by Sandou, Guillaume

Table of Contents: “…Ant colony optimization…”
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Optimization of Computer Networks : Modeling and Algorithms: a Hands-On Approach. by Pavón Mariño, Pablo

Table of Contents: “…Chapter 9: Primal Gradient Algorithms -- 9.1 Introduction -- 9.2 Penalty Methods -- 9.3 Adaptive Bifurcated Routing -- 9.4 Congestion Control using Barrier Functions -- 9.5 Persistence Probability Adjustment in MAC Protocols -- 9.6 Transmission Power Assignment in Wireless Networks -- 9.7 Notes and Sources -- 9.8 Exercises -- References -- Chapter 10: Dual Gradient Algorithms -- 10.1 Introduction -- 10.2 Adaptive Routing in Data Networks -- 10.3 Backpressure (Center-Free) Routing -- 10.4 Congestion Control -- 10.5 Decentralized Optimization of CSMA Window Sizes -- 10.6 Notes and Sources…”
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Digital Video and HD : Algorithms and Interfaces. by Poynton, Charles

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Network Routing : Algorithms, Protocols, and Architectures. by Medhi, Deep

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Practical Algorithms for 3D Computer Graphics, Second Edition. by Ferguson, R. Stuart (Robin Stuart), 1953-

Table of Contents: “…Basic theory and mathematical results; 3. Data structures for 3D graphics; 4. Basic visualization; 5. …”
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Digital is destroying everything : what the tech giants won't tell you about how robots, big data, and algorithms are radically remaking your future / by Edwards, Andrew V., 1956-

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The data imperative : how digitalization is reshaping management, organizing, and work by Schildt, Henri

Table of Contents: “…Cover -- The Data Imperative: How Digitalization is Reshaping Management, Organizing, and Work -- Copyright -- Acknowledgements -- Contents -- List of Figures -- List of Tables -- List of Boxes -- Chapter 1: Digital Transformation -- From Business Computing to the Digital Transformation -- Ubiquity and the Value of Digital Data in Business -- From Human Routines to Algorithmic Processing -- Digitalization as a Change in the Mindset and Norms of Management -- Data as a Management Priority -- Outline of the Chapters -- Digital Transformation and the Future of Work…”
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Data Mining : Practical Machine Learning Tools and Techniques, Second Edition. by Witten, I. H. (Ian H.)

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Data mining : practical machine learning tools and techniques by Witten, I. H. (Ian H.), Frank, Eibe, Hall, Mark A. (Mark Andrew)

Table of Contents: “…-- Input : concepts, instances, and attributes -- Output : knowledge representation -- Algorithms : the basic methods -- Credibility : evaluating what's been learned -- Implementations : real machine learning schemes -- Data transformation -- Ensemble learning -- Moving on : applications and beyond -- Introduction to Weka -- The explorer -- The knowledge flow interface -- The experimenter -- The command-line interface -- Embedded machine learning -- Writing new learning schemes -- Tutorial exercises for the weka explorer.…”
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Data Love : the Seduction and Betrayal of Digital Technologies. by Simanowski, Roberto

Table of Contents: “…Data-Mining Business; 7. Social Engineers Without a Cause; 8. …”
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Data Mining : a Tutorial-Based Primer, Second Edition. by Roiger, Richard J.

Table of Contents: “…3.2 A BASIC COVERING RULE ALGORITHM3.3 GENERATING ASSOCIATION RULES; 3.3.1 Confidence and Support; 3.3.2 Mining Association Rules: An Example; 3.3.3 General Considerations; 3.4 THE K-MEANS ALGORITHM; 3.4.1 An Example Using K-means; 3.4.2 General Considerations; 3.5 GENETIC LEARNING; 3.5.1 Genetic Algorithms and Supervised Learning; 3.5.2 General Considerations; 3.6 CHOOSING A DATA MINING TECHNIQUE; 3.7 CHAPTER SUMMARY; 3.8 KEY TERMS; Section II: Tools for Knowledge Discovery; Chapter 4. …”
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Data Mining.

Table of Contents: “…-- Decision Tree Induction -- GINI Index -- Entropy -- Misclassification Measure -- Practical Issues Regarding Decision Trees -- Predictive Accuracy -- STOP Condition for Split -- Pruning Decision Trees -- Extracting Classification Rules from Decision Trees -- Advantages of Decision Trees -- Data Mining Techniques and Models -- Data Mining Methods -- Bayesian Classifier -- Artificial Neural Networks -- Perceptron -- Types of Artificial Neural Networks -- Probabilistic Neural Networks -- Some Neural Networks Applications -- Support Vector Machines -- Association Rule Mining -- Rule-Based Classification -- k-Nearest Neighbor -- Rough Sets -- Clustering -- Hierarchical Clustering -- Non-hierarchical/Partitional Clustering -- Genetic Algorithms -- Components of GAs -- Architecture of GAs -- Applications -- Classification Performance Evaluation -- Costs and Classification Accuracy -- ROC (Receiver Operating Characteristic) Curve -- Statistical Methods for Comparing Classifiers -- References -- Index.…”
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Data Science : The Executive Summary - a Technical Book for Non-Technical Professionals. by Cady, Field

Table of Contents: “…2.1.5 What Data Scientists Don't (Necessarily) Do -- 2.1.5.1 Working Without Data -- 2.1.5.2 Working with Data that Can't Be Interpreted -- 2.1.5.3 Replacing Subject Matter Experts -- 2.1.5.4 Designing Mathematical Algorithms -- 2.2 Data Science in an Organization -- 2.2.1 Types of Value Added -- 2.2.1.1 Business Insights -- 2.2.1.2 Intelligent Products -- 2.2.1.3 Building Analytics Frameworks -- 2.2.1.4 Offline Batch Analytics -- 2.2.2 One-Person Shops and Data Science Teams -- 2.2.3 Related Job Roles -- 2.2.3.1 Data Engineer -- 2.2.3.2 Data Analyst -- 2.2.3.3 Software Engineer…”
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