Extraction of Quantifiable Information from Complex Systems

In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 "Mathematical Methods for Extracting Quantifiable Information from Complex Systems." This volume presents a comprehensive overview of the most important results obtained over the course of the pro...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Dahlke, Stephan (Editor ), Dahmen, Wolfgang (Editor ), Griebel, Michael (Editor ), Hackbusch, Wolfgang (Editor ), Ritter, Klaus (Editor ), Schneider, Reinhold (Editor ), Schwab, Christoph (Editor ), Yserentant, Harry (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Lecture Notes in Computational Science and Engineering, 102
Temas:
Differential equations.
Mathematics.
Mathematics-Data processing.
Numerical analysis.
Probabilities.
Approximation theory.
Differential Equations.
Applications of Mathematics.
Computational Mathematics and Numerical Analysis.
Numerical Analysis.
Probability Theory.
Approximations and Expansions.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • D. Belomestny, C. Bender, F. Dickmann, and N. Schweizer: Solving Stochastic Dynamic Programs by Convex Optimization and Simulation
  • W. Dahmen, C. Huang, G. Kutyniok, W
  • Q Lim, C. Schwab, and G. Welper: Efficient Resolution of Anisotropic Structures
  • R. Ressel, P. Dülk, S. Dahlke, K. S. Kazimierski, and P. Maass: Regularity of the Parameter-to-state Map of a Parabolic Partial Differential Equation
  • N. Chegini, S. Dahlke, U. Friedrich, and R. Stevenson: Piecewise Tensor Product Wavelet Bases by Extensions and Approximation Rates
  • P. A. Cioica, S. Dahlke, N. Döhring, S. Kinzel, F. Lindner, T. Raasch, K. Ritter, and R. Schilling: Adaptive Wavelet Methods for SPDEs
  • M. Altmayer, S. Dereich, S. Li, T. Müller-Gronbach, A. Neuenkirch, K. Ritter and L. Yaroslavtseva: Constructive Quantization and Multilevel Algorithms for Quadrature of Stochastic Differential Equations
  • O. G. Ernst, B. Sprungk, and H
  • J. Starkloff: Bayesian Inverse Problems and Kalman Filters
  • J. Diehl, P. Friz, H. Mai, H. Oberhauser, S. Riedel, and W. Stannat: Robustness in Stochastic Filtering and Maximum Likelihood Estimation for SDEs
  • J. Garcke and I. Klompmaker: Adaptive Sparse Grids in Reinforcement Learning
  • J. Ballani, L. Grasedyck, and M. Kluge: A Review on Adaptive Low-Rank Approximation Techniques in the Hierarchical Tensor Format
  • M. Griebel, J. Hamaekers, and F. Heber: A Bond Order Dissection ANOVA Approach for Efficient Electronic Structure Calculations
  • W. Hackbusch and R. Schneider: Tensor Spaces and Hierarchical Tensor Representations
  • L. Jost, S. Setzer, and M. Hein: Nonlinear Eigenproblems in Data Analysis - Balanced Graph Cuts and the Ratio DCA-Prox
  • M. Guillemard, D. Heinen, A. Iske, S. Krause-Solberg, and G. Plonka: Adaptive Approximation Algorithms for Sparse Data Representation
  • T. Jahnke and V. Sunkara: Error Bound for Hybrid Models of Two-scaled Stochastic Reaction Systems
  • R. Kiesel, A. Rupp, and K. Urban: Valuation of Structured Financial Products by Adaptive Multi wavelet Methods in High Dimensions
  • L Kämmerer, S. Kunis, I. Melzer, D. Potts, and T. Volkmer: Computational Methods for the Fourier Analysis of Sparse High-Dimensional Functions
  • E. Herrholz, D. Lorenz, G. Teschke, and D. Trede: Sparsity and Compressed Sensing in Inverse Problems
  • C. Lubich: Low-Rank Dynamics
  • E. Novak and D. Rudolf: Computation of Expectations by Markov Chain Monte Carlo Methods
  • H. Yserentant: Regularity, Complexity, and Approximability of Electronic Wave functions
  • Index.

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