Journal: Oberwolfach Report

Abbreviation

Oberwolfach Rep.

Publisher

EMS Publishing House

Journal Volumes

ISSN

1660-8941
1660-8933

Description

Filters

2005 - 200982010 - 201717
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Publications1 - 10 of 25
  • Bounded Cohomology and Applications
    Item type: Conference Paper
    Burger, Marc (2008)
    Oberwolfach Report
  • Sparse Quadrature Approach to Bayesian Inverse Problems
    Item type: Conference Paper
    Schwab, Christoph; Schillings, Claudia (2013)
    Oberwolfach Report
    High-dimensional problems appear naturally in various scientific areas, such as PDEs describing complex processes in computational chemistry and physics, or stochastic or parameter-dependent PDEs leading to deterministic problems with a large number of variables. Other highly visible examples are regression and classification with high-dimensional data as input and/or output in the context of learning theory. High dimensional problems cannot be solved by traditional numerical techniques, because of the so-called curse of dimensionality. Such problems therefore amplify the need for novel theoretical and computational approaches, in order to make them, first of all, tractable and, second, offering finer and finer resolutions of relevant features. Paradoxically, increasing computational power serves to even heighten this demand. The wealth of available data itself becomes a major obstruction. Extracting essential information from complex structures and developing rigorous models to quantify the quality of information in a high dimensional context leads to tasks that are not tractable by existing methods. The last decade has seen the emergence of several new computational methodologies to address the above obstacles. Their common features are the nonlinearity of the solution methods as well as the ability of separating solution characteristics living on different length scales. Perhaps the most prominent examples lie in adaptive grid solvers, tensor product, sparse grid and hyperbolic wavelet approximations and model reduction approaches. These have drastically advanced the frontiers of computability for certain problem classes in numerical analysis. This workshop deepened the understanding of the underlying mathematical concepts that drive this new evolution of computation and promoted the exchange of ideas emerging in various disciplines about the handling of multiscale and high-dimensional problems.
  • Separable regularization penalties and structured sparsity
    Item type: Other Conference Item
    van de Geer, Sara (2012)
    Oberwolfach Report
    The goal of this workshop was to discuss recent developments of nonparametric statistical inference. A particular focus was on high dimensional statistics, semiparametrics, adaptation, nonparametric bayesian statistics, shape constraint estimation and statistical inverse problems. The close interaction of these issues with optimization, machine learning and inverse problems has been addressed as well.
  • A Bound for the Empirical Risk Minimizer
    Item type: Conference Paper
    van de Geer, Sara (2006)
    Oberwolfach Report
  • Statistical inference for high-dimensional estimation of the inverse covariance matrix
    Item type: Conference Paper
    Janková, Jana (2014)
    Oberwolfach Report
  • Exterior Shape Calculus
    Item type: Conference Paper
    Hiptmair, Ralf (2017)
    Oberwolfach Report ~ Computational Inverse Problems for Partial Differential Equations
  • Multiple Traces Boundary Integral Formulation for Helmholtz Transmission Problems
    Item type: Other Conference Item
    Jerez-Hanckes, Carlos; Hiptmair, Ralf (2010)
    Oberwolfach Report ~ Computational Electromagnetism and Acoustics
  • Injective hulls of word hyperbolic groups
    Item type: Other Conference Item
    Lang, Urs (2010)
    Oberwolfach Report
  • The Mathematics and Statistics of Quantitative Risk Management
    Item type: Conference Proceedings
    Davis, Richard A.; Embrechts, Paul; Mikosch, Thomas (2012)
    Oberwolfach Report
    It was the aim of this workshop to gather a multidisciplinary and international group of scientists at the forefront of research in areas related to the mathematics and statistics of quantitative risk management. The main objectives of this workshop were to break down disciplinary barriers that often limit collaborative research in quantitative risk management, and to communicate the state of the art research from the different disciplines, and to point towards new directions of research.
  • A frame energy for tori immersed in R m : sharp Willmore-conjecture type lower bound, regularity of critical points and applications
    Item type: Conference Paper
    Mondino, Andrea; Rivière, Tristan (2013)
    Oberwolfach Report
Publications1 - 10 of 25