Search Results - (((((((ant OR find) OR spanning) OR arte) OR cantor) OR anne) OR cartsr) OR santo) algorithms.

Ant Colony Optimization and Constraint Programming. by Solnon, Christine

Table of Contents: “…Constraint programming; 1.1.2. Ant colony optimization; 1.1.3. Constraint programming with ant colony optimization; Chapter 2. …”
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Theory of randomized search heuristics : foundations and recent developments

Table of Contents: “…Runtime Analysis of Evolutionary Algorithms for Discrete Optimization Peter S. Oliveto and Xin Yao; 3. …”
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How to guard an art gallery and other discrete mathematical adventures by Michael, T. S., 1960-

Table of Contents: “…s Formula: Second Proof -- 2.8 Batting Averages and Lattice Points -- 2.9 Three Dimensions and N-largements -- 2.10 Notes and References -- 2.11 Problems -- 3 How to Guard an Art Gallery -- 3.1 The Sunflower Art Gallery -- 3.2 Art Gallery Problems -- 3.3 The Art Gallery Theorem -- 3.4 Colorful Consequences -- 3.5 Triangular and Chromatic Assumptions -- 3.6 Modern Art Galleries -- 3.7 Art Gallery Sketches -- 3.8 Right-Angled Art Galleries -- 3.9 Guarding the Guards -- 3.10 Three Dimensions and the Octoplex…”
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Flowchart and Algorithm Basics : The Art of Programming. by Chaudhuri, A. B.

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The Human Algorithm by Solis, Brian

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Probability and Algorithms. by Staff, National Research Council

Table of Contents: “…""PROBABILITY AND ALGORITHMS""; ""Copyright""; ""Preface""; ""Contents""; ""1. …”
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Algorithms in Bioinformatics : a Practical Introduction by Sung, Wing-Kin

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Convergence theorems for lattice group-valued measures. by Antonio Boccuto; Xenofon Dimitriou

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Algorithms for Dummies. by Mueller, John Paul

Table of Contents: “…Intro -- Title Page -- Copyright Page -- Table of Contents -- Introduction -- About This Book -- Foolish Assumptions -- Icons Used in This Book -- Beyond the Book -- Where to Go from Here -- Part 1 Getting Started with Algorithms -- Chapter 1 Introducing Algorithms -- Describing Algorithms -- The right way to make toast: Defining algorithm uses -- Finding algorithms everywhere -- Using Computers to Solve Problems -- Getting the most out of modern CPUs and GPUs -- Working with special-purpose chips -- Networks: Sharing is more than caring -- Leveraging available data…”
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Algorithmic composition : a guide to composing music with Nyquist by Simoni, Mary Hope

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Nature-inspired optimization algorithms by Yang, Xin-She

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Finding Alphas : a Quantitative Approach to Building Trading Strategies. by Tulchinsky, Igor

Table of Contents: “…Data Inputs to an AlphaAlpha Universe; Alpha Prediction Frequency; Value of an Alpha; Practical Alpha Evaluation; Future Performance; Conclusion; 5 How to Develop an Alpha: A Case Study; Conclusion; 6 Data and Alpha Design; How we find Data for Alphas; Data Validation; Understand the Data Before Using it; Embrace the Big Data ERA; Conclusion; 7 Turnover; Alpha Horizon; The Cost of a Trade; The Crossing Effect; Controlling Turnover; Examples; Tuning the Turnover; 8 Alpha Correlation; Alpha PnL Correlation; Alpha Value Correlation; Correlation with Alpha Pool; Conclusion…”
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Open Data Structures : an Introduction. by Morin, Pat

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Swarm intelligence and bio-inspired computation : theory and applications

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Ant colony optimization by Dorigo, Marco

Table of Contents: “…Preface; Acknowledgments; 1 -- From Real to Artificial Ants; 2 -- The Ant Colony Optimization Metaheuristic; 3 -- Ant Colony Optimization Algorithms for the Traveling Salesman Problem; 4 -- Ant Colony Optimization Theory; 5 -- Ant Colony Optimization for NP-Hard Problems; 6 -- AntNet: An ACO Algorithm for Data Network Routing; 7 -- Conclusions and Prospects for the Future; Appendix: Sources of Information about the ACO Field; References; Index.…”
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Stabilisation and Motion Control of Unstable Objects by Formalʹskiĭ, A. M. (Aleksandr Moiseevich)

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The golden ticket : P, NP, and the search for the impossible by Fortnow, Lance, 1963-

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Introduction to cryptography by Padhye, Sahadeo, Sahu, Rajeev A., Saraswat, Vishal

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Mastering Machine Learning Algorithms : Expert techniques to implement popular machine learning algorithms and fine-tune your models. by Bonaccorso c/o Quandoo, Giuseppe

Table of Contents: “…Conditional probabilities and Bayes' theoremBayesian networks; Sampling from a Bayesian network; Direct sampling; Example of direct sampling; A gentle introduction to Markov chains; Gibbs sampling; Metropolis-Hastings sampling; Example of Metropolis-Hastings sampling; Sampling example using PyMC3; Hidden Markov Models (HMMs); Forward-backward algorithm; Forward phase; Backward phase; HMM parameter estimation; Example of HMM training with hmmlearn; Viterbi algorithm; Finding the most likely hidden state sequence with hmmlearn; Summary; Chapter 5: EM Algorithm and Applications.…”
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Pathway modeling and algorithm research

Table of Contents: “…PATHWAY MODELING AND ALGORITHM RESEARCH; PATHWAY MODELING AND ALGORITHM RESEARCH; Contents; Preface; Biological Pathways and Their Modeling; Abstract; 1. …”
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