Search Results - (((((((kant OR monte) OR mantis) OR akantu) OR cantor) OR anne) OR shape) OR hints) algorithms.

Building winning algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading / by Davey, Kevin J., 1966-

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Algorithms of education : how datafication and artificial intelligence shape policy / by Gulson, Kalervo N., Sellar, Sam, Webb, P. Taylor

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Theory of randomized search heuristics : foundations and recent developments

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Algorithmic Puzzles. by Levitin, Anany, Levitin, Maria

Table of Contents: “…-- General strategies for algorithm design -- Analysis techniques -- Easier puzzles (#1 to #50) -- Puzzles of medium difficulty (#51 to #110) -- Harder puzzles (#111 to #150) -- Hints -- Solutions -- References -- Design stragety and analysis index.…”
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The rise of the algorithms : how YouTube and TikTok conquered the world by Jordan, John M.

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Derivatives algorithms. Volume 1, Bones by Hyer, Tom

Table of Contents: “…Customizing vectors. 4.2. Algorithms. 4.3. Matrices and square matrices. 4.4. …”
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Algorithmic composition : a guide to composing music with Nyquist by Simoni, Mary Hope

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Permutation Group Algorithms by Seress, kos

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Nature-inspired optimization algorithms by Yang, Xin-She

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Multi-Objective Optimization in Theory and Practice II : metaheuristic algorithms. by Keller, André A.

Table of Contents: “…Near Pareto-Optimal Front; 1.3.4. Shapes of a Pareto-Optimal Front; 1.4. Selection Procedures of Algorithms; 1.4.1. …”
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Algorithms in invariant theory by Sturmfels, Bernd, 1962-

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Handbook of Markov chain Monte Carlo

Table of Contents: “…Foundations, methodology, and algorithms.…”
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Quantum Monte Carlo : origins, development, applications

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Fast sequential Monte Carlo methods for counting and optimization by Rubinstein, Reuven Y.

Table of Contents: “…4.3 Splitting Algorithm with Fixed Levels4.4 Adaptive Splitting Algorithm; 4.5 Sampling Uniformly on Discrete Regions; 4.6 Splitting Algorithm for Combinatorial Optimization; 4.7 Enhanced Splitting Method for Counting; 4.8 Application of Splitting to Reliability Models; 4.9 Numerical Results with the Splitting Algorithms; 4.10 Appendix: Gibbs Sampler; Chapter 5: Stochastic Enumeration Method; 5.1 Introduction; 5.2 OSLA Method and Its Extensions; 5.3 SE Method; 5.4 Applications of SE; 5.5 Numerical Results; Appendix A: Additional Topics; A.1 Combinatorial Problems; A.2 Information.…”
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Recent advances in quantum Monte Carlo methods. Part II

Table of Contents: “…2.1 Space-warp coordinate transformation3 Correlated sampling in diffusion Monte Carlo; 3.1 An impractical route to DMC correlated sampling; 3.2 Our accurate and efficient algorithm; 4 Secondary geometry wave functions; 5 Results; 6 Comparison to variance-reduced Hellman-Feynman method; 7 Conclusions; Acknowledgments; References; IMPROVED SCALING IN DIFFUSION QUANTUM MONTE CARLO WITH LOCALIZED MOLECULAR ORBITALS; 1 Introduction; 2 The Diffusion Quantum Monte Carlo Method; 3 Scaling of the Algorithm; 4 Test Calculations for Linear Hydrocarbons; 5 Conclusion; Acknowledgments; References.…”
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A guide to Monte Carlo simulations in statistical physics by Landau, David P.

Table of Contents: “…3.7 Finding the groundstate of a Hamiltonian -- 3.8 Generation of 'random' walks -- 3.8.1 Introduction -- 3.8.2 Random walks -- 3.8.3 Self-avoiding walks -- 3.8.4 Growing walks and other models -- 3.9 Final remarks -- References -- 4 Importance sampling Monte Carlo methods -- 4.1 Introduction -- 4.2 The simplest case: single spin-flip sampling for the simple Ising model -- 4.2.1 Algorithm -- 4.2.2 Boundary conditions -- 4.2.3 Finite size effects -- 4.2.4 Finite sampling time effects -- 4.2.5 Critical relaxation -- 4.3 Other discrete variable models.…”
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Black box classical groups by Kantor, W. M. (William M.), 1944-

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Evolutionary optimization algorithms by Simon, Dan, 1960-

Table of Contents: “…2.6.1 Biased Optimization Algorithms2.6.2 The Importance of Monte Carlo Simulations; 2.7 Intelligence; 2.7.1 Adaptation; 2.7.2 Randomness; 2.7.3 Communication; 2.7.4 Feedback; 2.7.5 Exploration and Exploitation; 2.8 Conclusion; Problems; PART II CLASSIC EVOLUTIONARY ALGORITHMS; 3 Genetic Algorithms; 3.1 The History of Genetics; 3.1.1 Charles Darwin; 3.1.2 Gregor Mendel; 3.2 The Science of Genetics; 3.3 The History of Genetic Algorithms; 3.4 A Simple Binary Genetic Algorithm; 3.4.1 A Genetic Algorithm for Robot Design; 3.4.2 Selection and Crossover; 3.4.3 Mutation; 3.4.4 GA Summary.…”
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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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Advanced Markov chain Monte Carlo methods : learning from past samples by Liang, F. (Faming), 1970-

Table of Contents: “…Advanced Markov Chain Monte Carlo Methods; Contents; Preface; Acknowledgments; Publisher's Acknowledgments; 1 Bayesian Inference and Markov Chain Monte Carlo; 2 The Gibbs Sampler; 3 The Metropolis-Hastings Algorithm; 4 Auxiliary Variable MCMC Methods; 5 Population-Based MCMC Methods; 6 Dynamic Weighting; 7 Stochastic Approximation Monte Carlo; 8 Markov Chain Monte Carlo with Adaptive Proposals; References; Index.…”
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