Prof. Dr. Bernard Haasdonk
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Prof. Dr.
Bernard Haasdonk Professor for Numerical Mathematics |
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| Phone | 0049 711 685 - 65542 | |
| Fax | 0049 711 685 - 65507 | |
| Room | Office 7.328 | |
| Email address | Link | |
| Address |
University of Stuttgart Institute of Applied Analysis and Numerical Simulation Pfaffenwaldring 57 D-70569 Stuttgart Germany |
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Research Interests
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Model Reduction
- Parametrized PDEs
- Parametrized dynamical systems
- Reduced basis methods
- Kernel methods for nonlinear systems
- Adaptive Basis Generation
- POD-Greedy procedures
-
Numerical Analysis
- Evolution schemes, FV, LDG-methods
- Conservation laws
- Variational inequalities
- Optimization with PDE constraints
- Kernel methods for function approximation / PDEs
- Greedy Procedures
-
Applications
- Transport problems, fluid dynamics, single-/two-phase flow
- Obstacle problems, Option Pricing
- Geometry parametrization and optimization
- Multiscale problems
- Elastic multibody systems
- Chemical Master Equation
- Fuel cells, Lithium-Ion cells
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Scientific Computing
- Multiresolution visualization
- Numerical Software development
- Grape/dune-rb/RBmatlab/KerMor
-
Machine Learning
- Kernel methods, kernel design
- Support vector machines
- Kernel Fisher / Mahalanobis Discriminants
- Proximity-based learning
-
Pattern Recognition
- Feature extraction
- Classifier design
- Invariance
- Image processing
- Handwriting Recognition
- Raman-Spectra Recognition
Publications
Dibak, C.; Schmidt, A.; Dürr, F.; Haasdonk, B. & Rothermel, K.:
Server-Assisted Interactive Mobile Simulations for Pervasive Applications,
Proceedings of the 15th IEEE International Conference on Pervasive Computing and Communications (PerCom),
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Germany,
IEEE,
2017, 1-10.
Martini, I.; Rozza, G. & Haasdonk, B.:
Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models,
Journal of Scientific Computing,
2017.
Santin, G. & Haasdonk, B.:
Convergence rate of the data-independent P-greedy algorithm in kernel-based approximation,
Dolomites Research Notes on Approximation,
2017, 10, 68-78.
Schmidt, A. & Haasdonk, B.:
Reduced basis approximation of large scale parametric algebraic Riccati equations,
ESAIM: Control, Optimisation and Calculus of Variations,
EDP Sciences,
2017.
Amsallem, D. & Haasdonk, B.:
PEBL-ROM: Projection-Error Based Local Reduced-Order Models,
AMSES, Advanced Modeling and Simulation in Engineering Sciences,
2016, 3.
Antoulas, A. C.; Haasdonk, B. & Peherstorfer, B.:
MORML 2016 Book of Abstracts,
University of Stuttgart,
2016.
Baur, U.; Benner, P.; Haasdonk, B.; Himpe, C.; Maier, I. & Ohlberger, M.:
P. Benner and A. Cohen and M. Ohlberger and K. Willcox (Eds.),
Comparison of methods for parametric model order reduction of instationary problems,
Model Reduction and Approximation for Complex Systems,
Birkhäuser Publishing,
2016.
Garmatter, D.; Haasdonk, B. & Harrach, B.:
A reduced Landweber Method for Nonlinear Inverse Problems,
Inverse Problems,
2016, 32, 1-21.
Redeker, M. & Haasdonk, B.:
A POD-EIM reduced two-scale model for precipitation in porous media,
MCMDS, Mathematical and Computer Modelling of Dynamical Systems,
2016.
Schmidt, A. & Haasdonk, B.:
Reduced basis method for H2 optimal feedback control problems,
IFAC-PapersOnLine,
2016, 49, 327 - 332.
Amsallem, D.; Farhat, C. & Haasdonk, B.:
Editorial: Special Issue on Modelling Reduction,
IJNME, International Journal of Numerical Methods in Engineering,
2015, 102, 931-932.
Burkovska, O.; Haasdonk, B.; Salomon, J. & Wohlmuth, B.:
Reduced basis methods for pricing options with the Black-Scholes and Heston model,
SIAM journal on Financial Mathematics (SIFIN),
Arxiv,
2015.
Dihlmann, M. A. & Haasdonk, B.:
Certified PDE-constrained parameter optimization using reduced basis surrogate models for evolution problems,
COAP, Computational Optimization and Applications,
2015, 60, 753-787.
Dihlmann, M. & Haasdonk, B.:
A reduced basis Kalman filter for parametrized partial differential equations,
ESAIM: Control, Optimisation and Calculus of Variations,
EDP Sciences,
2015.
Kaulmann, S.; Flemisch, B.; Haasdonk, B.; Lie, K.-A. & Ohlberger, M.:
The Localized Reduced Basis Multiscale method for two-phase flows in porous media,
Internat. J. Numer. Methods Engrg.,
2015, 102, 1018-1040.
Martini, I. & Haasdonk, B.:
Output Error Bounds for the Dirichlet-Neumann Reduced Basis Method,
Numerical Mathematics and Advanced Applications - ENUMATH 2013,
2015, 103, 437-445.
Martini, I.; Rozza, G. & Haasdonk, B.:
Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system,
Advances in Computational Mathematics,
2015, 41, 1131-1157.
Redeker, M. & Haasdonk, B.:
A POD-EIM reduced two-scale model for crystal growth,
Advances in Computational Mathematics,
Springer US,
2015, 41, 987-1013.
Schmidt, A.; Dihlmann, M. & Haasdonk, B.:
Basis generation approaches for a reduced basis linear quadratic regulator,
Proc. MATHMOD 2015 - 8th Vienna International Conference on Mathematical Modelling,
2015, 713-718.
Wirtz, D.; Karajan, N. & Haasdonk, B.:
Surrogate Modelling of multiscale models using kernel methods,
International Journal of Numerical Methods in Engineering,
2015, 101, 1-28.
Haasdonk, B. & Ohlberger, M.:
Wenn die Probleme zahlreicher werden: Reduzierte Basis Methoden für effiziente und gesicherte numerische Simulation,
GAMM Rundbrief,
2014, 2014, 6-13.
Maier, I. & Haasdonk, B.:
A Dirichlet-Neumann reduced basis method for homogeneous domain decomposition problems,
Applied Numerical Mathematics,
2014, 78, 31-48.
Wirtz, D.; Sorensen, D. & Haasdonk, B.:
A Posteriori Error Estimation for DEIM Reduced Nonlinear Dynamical Systems,
SIAM Journal on Scientific Computing,
Society for Industrial & Applied Mathematics (SIAM),
2014, 36, A311-A338.
Wirtz, D.; Sorensen, D. & Haasdonk, B.:
A-posteriori error estimation for DEIM reduced nonlinear dynamical systems,
SIAM J. Sci. Comp.,
University of Stuttgart,
2014, 36, A311-A338.
Amsallem, D.; Haasdonk, B. & Rozza, G.:
A Conference within a Conference for MOR Researchers,
SIAM News,
2013, 46, 8.
Dihlmann, M. & Haasdonk, B.:
Certified Nonlinear Parameter Optimization with Reduced Basis Surrogate Models,
PAMM, Proc. Appl. Math. Mech., Special Issue: 84th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Novi Sad 2013; Editors: L. Cvetković, T. Atanacković and V. Kostić,
2013, 13, 3-6.
Dihlmann, M. & Haasdonk, B.:
Certified Nonlinear Parameter Optimization with Reduced Basis Surrogate Models,
PAMM, Proc. Appl. Math. Mech., Special Issue: 84th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Novi Sad 2013; Editors: L. Cvetković, T. Atanacković and V. Kostić,
2013, 13, 3-6.
Fehr, J.; Fischer, M.; Haasdonk, B. & Eberhard, P.:
Greedy-based Approximation of Frequency-weighted Gramian Matrices for Model Reduction in Multibody Dynamics,
ZAMM,
2013, 93, 501-519.
Haasdonk, B.:
Convergence Rates of the POD--Greedy Method,
ESAIM: Mathematical Modelling and Numerical Analysis,
EDP Sciences,
2013, 47, 859-873.
Haasdonk, B.; Urban, K. & Wieland, B.:
Reduced basis methods for parametrized partial differential equations with stochastic influences using the Karhunen Loeve expansion,
SIAM/ASA J. Unc. Quant.,
2013, 1, 79-105.
Kaulmann, S. & Haasdonk, B.:
Moitinho de Almeida, José Paulo Baptista and Diez, Pedro and Tiago, Carlos and Parés, Núria (Eds.),
Online Greedy Reduced Basis Construction Using Dictionaries,
VI International Conference on Adaptive Modeling and Simulation (ADMOS 2013),
2013, 365-376.
Wirtz, D. & Haasdonk, B.:
A Vectorial Kernel Orthogonal Greedy Algorithm,
Dolomites Res. Notes Approx.,
2013, 6, 83-100.
Albrecht, F.; Haasdonk, B.; Kaulmann, S. & Ohlberger, M.:
Handloviv cová, Angela and Minarechová, Zuzana and v Sevv coviv c, Daniel (Eds.),
The Localized Reduced Basis Multiscale Method,
Algoritmy 2012,
Publishing House of STU,
2012, 393-403.
Dihlmann, M.; Kaulmann, S. & Haasdonk, B.:
Online Reduced Basis Construction Procedure for Model Reduction of Parametrized Evolution Systems,
Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling,
2012.
Drohmann, M.; Haasdonk, B. & Ohlberger, M.:
Dedner, Andreas and Flemisch, Bernd and Klöfkorn, Robert (Eds.),
A Software Framework for Reduced Basis Methods Using DUNE-RB and RBMATLAB,
Advances in DUNE: Proceedings of the DUNE User Meeting, Held in October 6th-8th 2010 in Stuttgart, Germany,
Springer,
2012.
Drohmann, M.; Haasdonk, B. & Ohlberger, M.:
Reduced Basis Model Reduction of Parametrized Two-phase Flow in Porous Media,
Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling,
2012.
Drohmann, M.; Haasdonk, B. & Ohlberger, M.:
Reduced Basis Approximation for Nonlinear Parametrized Evolution Equations based on Empirical Operator Interpolation,
SIAM J. Sci. Comput.,
2012, 34, A937-A969.
Haasdonk, B.; Salomon, J. & Wohlmuth, B.:
A Reduced Basis Method for Parametrized Variational Inequalities,
SIAM Journal on Numerical Analysis,
2012, 50, 2656-2676.
Haasdonk, B.; Salomon, J. & Wohlmuth, B.:
A Reduced Basis Method for the Simulation of American Options,
ENUMATH 2011 Proceedings,
2012.
Ruiner, T.; Fehr, J.; Haasdonk, B. & Eberhard, P.:
A-posteriori error estimation for second order mechanical systems,
Acta Mechanica Sinica,
2012, 28(3), 854-862.
Waldherr, S. & Haasdonk, B.:
Efficient Parametric Analysis of the Chemical Master Equation through Model Order Reduction,
BMC Systems Biology,
2012, 6, 81.
Wirtz, D. & Haasdonk, B.:
A-posteriori error estimation for parameterized kernel-based systems,
Proc. MATHMOD 2012 - 7th Vienna International Conference on Mathematical Modelling,
2012.
Wirtz, D. & Haasdonk, B.:
Efficient a-posteriori error estimation for nonlinear kernel-based reduced systems,
Systems and Control Letters,
2012, 61, 203 - 211.
Dihlmann, M.; Drohmann, M. & Haasdonk, B.:
Model Reduction of Parametrized Evolution Problems using the Reduced basis Method with Adaptive Time-Partitioning,
Proc. of ADMOS 2011,
2011.
Drohmann, M.; Haasdonk, B. & Ohlberger, M.:
Adaptive Reduced Basis Methods for Nonlinear Convection-Diffusion Equations,
In Proc. FVCA6,
2011.
Haasdonk, B.; Dihlmann, M. & Ohlberger, M.:
A Training Set and Multiple Basis Generation Approach for Parametrized Model Reduction Based on Adaptive Grids in Parameter Space,
Mathematical and Computer Modelling of Dynamical Systems,
2011, 17, 423-442.
Haasdonk, B. & Lohmann, B.:
Special Issue on ''Model Order Reduction of Parametrized Problems'',
Mathematical and Computer Modelling of Dynamical Systems,
2011, 17, 295-296.
Haasdonk, B. & Ohlberger, M.:
Efficient reduced models and it a posteriori error estimation for parametrized dynamical systems by offline/online decomposition,
Math. Comput. Model. Dyn. Syst.,
2011, 17, 145-161.
Jung, N.; Patera, A.; Haasdonk, B. & Lohmann, B.:
Model Order Reduction and Error Estimation with an Application to the Parameter-Dependent Eddy Current Equation,
Mathematical and Computer Modelling of Dynamical Systems,
2011, 17, 561-582.
Kaulmann, S.; Ohlberger, M. & Haasdonk, B.:
A new local reduced basis discontinuous Galerkin approach for heterogeneous multiscale problems,
Comptes Rendus Mathematique,
2011, 349, 1233-1238.
Haasdonk, B.:
Effiziente und Gesicherte Modellreduktion für Parametrisierte Dynamische Systeme.,
at - Automatisierungstechnik,
2010, 58, 468-474.
Pekalska, E. & Haasdonk, B.:
Indefinite Kernel Discriminant Analysis,
Proc. COMPSTAT 2010, International Conference on Computational Statistics,
2010.
Haasdonk, B. & Ohlberger, M.:
Space-Adaptive Reduced Basis Simulation for Time-Dependent Problems,
Proc. MATHMOD 2009, 6th Vienna International Conference on Mathematical Modelling,
2009.
Haasdonk, B. & Ohlberger, M.:
Efficient Reduced Models for Parametrized Dynamical Systems by Offline/Online Decomposition,
Proc. MATHMOD 2009, 6th Vienna International Conference on Mathematical Modelling,
2009.
Haasdonk, B. & Ohlberger, M.:
Efficient a-posteriori Error Estimation for Parametrized Reduced Dynamical Systems,
GMA-Fachaussschuss 1.30, Tagungsband,
2009.
Haasdonk, B. & Ohlberger, M.:
Reduced basis method for explicit finite volume approximations of nonlinear conservation laws,
Hyperbolic problems: theory, numerics and applications,
Amer. Math. Soc.,
2009, 67, 605-614.
Haasdonk, B.; Ohlberger, M.; Tonn, T. & Urban, K.:
MoRePaS 2009 Book of Abstracts,
University of Münster,
2009.
Jung, N.; Haasdonk, B. & Kröner, D.:
Reduced Basis Method for Quadratically Nonlinear Transport Equations,
IJCSM,
2009, 2, 334-353.
Pekalska, E. & Haasdonk, B.:
Kernel Discriminant Analysis with Positive Definite and Indefinite Kernels,
IEEE Transactions on Pattern Analysis and Machine Intelligence,
2009, 31, 1017-1032.
Drohmann, M.; Haasdonk, B. & Ohlberger, M.:
Reduced Basis Method for Finite Volume Approximation of Evolution Equations on Parametrized Geometries,
Proceedings of ALGORITMY 2009,
2008, 111-120.
Haasdonk, B. & Ohlberger, M.:
Reduced basis method for finite volume approximations of parametrized linear evolution equations,
ESAIM: M2AN,
2008, 42, 277-302.
Haasdonk, B. & Ohlberger, M.:
Adaptive basis enrichment for the reduced basis method applied to finite volume schemes,
Finite volumes for complex applications V,
ISTE, London,
2008, 471-478.
Haasdonk, B.; Ohlberger, M. & Rozza, G.:
A Reduced Basis Method for Evolution Schemes with Parameter-Dependent Explicit Operators,
ETNA, Electronic Transactions on Numerical Analysis,
2008, 32, 145-161.
Haasdonk, B. & Pekalska, E.:
Indefinite Kernel Fisher Discriminant,
Proc. ICPR 2008, International Conference on Pattern Recognition,
2008.
Haasdonk, B. & Pekalska, E.:
Classification with Kernel Mahalanobis Distances,
Proc. of 32nd. GfKl Conference, Advances in Data Analysis, Data Handling and Business Intelligence,
2008.
Fuhrmann J; Haasdonk, B.; Holzbecher, E. & Ohlberger, M.:
Guest Editorial for Special Issue on Modelling and Simulation of PEM-FC,
Journal of Fuel Cell Science and Technology,
2007.
Haasdonk, B. & Burkhardt, H.:
Classification with Invariant Distance Substitution Kernels,
Proc. of 31st GfKl Conference, Data Analysis, Machine Learning, and Applications,
2007.
Haasdonk, B. & Burkhardt, H.:
Invariant Kernels for Pattern Analysis and Machine Learning,
Machine Learning,
IIF-LMB, Universität Freiburg, Institut für Informatik,
2007, 68, 35-61.
Haasdonk, B. & Ohlberger, M.:
P. Díez and K. Runesson (Eds.),
Basis Construction for Reduced Basis Methods By Adaptive Parameter Grids,
Proc. International Conference on Adaptive Modeling and Simulation, ADMOS 2007,
CIMNE, Barcelona,
2007.
Peschke, K.-D.; Haasdonk, B.; Ronneberger, O.; Burkhard, H.; Rösch, P.; Harz, M. & Popp, J.:
Using Transformation Knowledge for the Classification of Raman Spectra of Biological Samples,
BIOMED 2006, Proc. of the 4th IASTED International Conference on Biomedical Engineering,
2006, 288-293.
Haasdonk, B.:
Feature Space Interpretation of SVMs with Indefinite Kernels,
IEEE Transactions on Pattern Analysis and Machine Intelligence,
IEEE Computer Society,
2005, 27, 482-492.
Haasdonk, B.; Vossen, A. & Burkhardt, H.:
Invariance in Kernel Methods by Haar-Integration Kernels,
Proceedings of the 14th Scandinavian Conference on Image Analysis,
Springer,
2005.
Haasdonk, B. & Bahlmann, C.:
Learning with Distance Substitution Kernels,
Pattern Recognition - Proceedings of the 26th DAGM Symposium,
Springer,
2004, 220-227.
Haasdonk, B.; Halawani, A. & Burkhardt, H.:
Adjustable invariant features by partial Haar-integration,
Proceedings of the 17th International Conference on Pattern Recognition,
2004, 2, 769- 774.
Haasdonk, B.; Ohlberger, M.; Rumpf, M.; Schmidt, A. & Siebert, K. G.:
Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations,
Computing,
2003, 70, 181-204.
Bahlmann, C.; Haasdonk, B. & Burkhardt, H.:
On-line Handwriting Recognition with Support Vector Machines - A Kernel Approach,
Proc. of the 8th International Workshop on Frontiers in Handwriting Recognition,
IEEE Computer Society,
2002, 49-54.
Haasdonk, B. & Keysers, D.:
Tangent Distance Kernels for Support Vector Machines,
Proceedings of the 16th International Conference on Pattern Recognition,
IEEE Computer Society,
2002, 2, 864-868.
Haasdonk, B.; Kröner, D. & Rohde, C.:
Convergence of a staggered Lax-Friedrichs scheme for nonlinear conservation laws on unstructured two-dimensional grids,
Numer. Math.,
2001, 88, 459-484.
Haasdonk, B.:
Convergence of a Staggered Lax-Friedrichs Scheme on Unstructured 2D-Grids,
HYP 2000, Proceedings of the 8th International Conference on Hyperbolic Problems,
Birkhäuser,
2000, 2, 475-484.
Haasdonk, B.:
Konvergenz eines Staggered Lax-Friedrichs Verfahrens auf unstrukturierten 2D Gittern,
Universität Freiburg, Abteilung für Angewandte Mathematik,
1999.
Haasdonk, B.:
Transformation Knowledge in Pattern Analysis with Kernel Methods, Distance and Integration Kernels,
Albert-Ludwigs-Universität, Freiburg im Breisgau, Fakultät für Angewandte Wissenschaften,
2005.
Recent Preprints and Miscellaneous
Haasdonk, B. & Santin, G.:
Greedy Kernel Approximation for Sparse Surrogate Modelling,
2017.
Martini, I.; Rozza, G. & Haasdonk, B.:
Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models,
Journal of Scientific Computing,
2017.
Wittwar, D.; Schmidt, A. & Haasdonk, B.:
Reduced Basis Approximation for the Discrete-time Parametric Algebraic Riccati Equation,
University of Stuttgart,
2017.
Alla, A.; Schmidt, A. & Haasdonk, B.:
Model order reduction approaches for infinite horizon optimal control problems via the HJB equation,
University of Stuttgart,
2016.
Carlberg, K.; Brencher, L.; Haasdonk, B. & Barth, A.:
Data-driven time parallelism via forecasting,
2016.
Fritzen, F.; Haasdonk, B.; Ryckelynck, D. & Schöps, S.:
An algorithmic comparison of the Hyper-Reduction and the Discrete Empirical Interpolation Method for a nonlinear thermal problem,
University of Stuttgart,
2016.
Haasdonk, B.:
Reduced Basis Methods for Parametrized PDEs -- A Tutorial Introduction for Stationary and Instationary Problems,
IANS, University of Stuttgart, Germany,
2014.
Haasdonk, B.; Salomon, J. & Wohlmuth, B.:
A Reduced Basis Method for Parametrized Variational Inequalities,
University of Stuttgart,
2012.
Haasdonk, B.:
Reduzierte-Basis-Methoden, Vorlesungsskript SS 2011,
University of Stuttgart,
2011.
Pekalska, E. & Haasdonk, B.:
Kernel Quadratic Discriminant Analysis with Positive and Indefinite Kernels,
University of Münster,
2008.
Haasdonk, B.; Ohlberger, M. & Rozza, G.:
A Reduced Basis Method for Evolution Schemes with Parameter-Dependent Explicit Operators,
University of Münster,
2007.
Haasdonk, B. & Ohlberger, M.:
Reduced Basis Method for Finite Volume Approximations of Parametrized Evolution Equations,
University of Freiburg, Institute of Applied Mathematics,
2006.
Burkhardt, H. & Haasdonk, B.:
Mustererkennung WS 02/03, ein multimedialer Grundlagenkurs im Hauptstudium Informatik,
2003.
Haasdonk, B.; Poluru, B. & Teynor, A.:
Presto-Box 1.1 Library Documentation,
IIF-LMB, Universität Freiburg,
2003.
Haasdonk, B.; Ohlberger, M.; Rumpf, M.; Schmidt, A. & Siebert, K.-G.:
h-p-Multiresolution Visualization of Adaptive Finite Element Simulations,
Mathematics Department, University of Freiburg,
2001.
Geßner, T.; Haasdonk, B.; Lenz, M.; Metscher, M.; Neubauer, R.; Ohlberger, M.; Rosenbaum, W.; Rumpf, M.; Schwörer, R.; Spielberg, M. & Weikard, U.:
A Procedural Interface for Multiresolutional Visualization of General Numerical Data,
University of Bonn,
1999.
Supervised Theses
Garikapati, H.:
A PGD Based Preconditioner for Scalar Elliptic Problems,
University of Stuttgart,
2014.
Staehle, M.:
Anisotrope Diffusion zur Bildfilterung,
University of Stuttgart,
2014.
Sachs, A.:
Proper-Generalized-Decomposition-Methode für elliptische partielle Differentialgleichungen,
University of Stuttgart,
2013.
Simon, A.:
Vergleich zwischen dem Galerkinverfahren und dem Verfahren des minimalen Residuums im Zusammenhang mit der Reduzierte-Basis-Methode,
University of Stuttgart,
2013.
Simon, D.:
Algorithmen der gitterfreien Kollokation durch radiale Basisfunktionen,
University of Stuttgart,
2013.
Appel, C.:
Mathematische Methoden zur Bestimmung alterungskritischer Parameter von Lithium-Ionen Zellen,
IANS, University of Stuttgart,
2012.
Bernlöhr, J.:
Online Reduzierte Basis Generierung für Parameterabhängige Elliptische Partielle Differentialgleichungen,
IANS, University of Stuttgart,
2012.
Garmatter, D.:
Reduzierte Basis Methoden für lineare Evolutionsprobleme am Beispiel von European Option Pricing,
IANS, University of Stuttgart,
2012.
Maier:
Ein iteratives Gebietszerlegungsverfahren für die Reduzierte-Basis-Methode,
University of Stuttgart,
2011.
Ruiner, T.:
A-posteriori Fehlerschätzer für Reduzierte Mechanische Systeme zweiter Ordnung,
ITM, University of Stuttgart,
2011.
Schuster, D.:
SVD-basierte Modellreduktion für Elastische Mehrkörpersysteme,
IANS, University of Stuttgart,
2011.
Zeeb, O.:
Reduzierte Basis Modelle für Formoptimierung unter Verwendung des SQP-Algorithmus,
IANS, University of Stuttgart,
2011.
Teaching
Current Semester
See the teaching page.
Past Semester WS 2010/2011
Lecture Diskrete Strukturen
Seminar Angewandte Mathematik
Lab Computerpraktikum
SIMTECH-Netzwerk-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Past Semester SS 2010
Lecture Reduzierte-Basis-Methoden
Proseminar Numerik
SIMTECH-Netzwerk-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Past WS 2009/2010
Workshop at Fraunhofer Talentschool 2010, 12.-14.3.2010
Angewandte Mathematik: Modellierung und Simulation in Naturwissenschaften und Technik
Lecture Modellreduktion
Computerpraktikum Wissenschaftliches Rechnen
SIMTECH-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Lecturer Position
Teaching course Digitale Bildverarbeitung, WS 05/06, SS 2006, WS 06/07, SS 2007, WS 07/08, SS 2008 at the University of Applied Sciences Offenburg, Germany
Lectures
Lecture Einführung in die Modellreduktion, SS 2009
Tutorial Kernel Methods at IFCS@GFKL2009
Lecture Modellierung und Simulation von Straßenverkehr, Mathetage, University of Münster, 5.9.2008.
Assisting lecture Einführung in die Numerische Mathematik, WS 07/08
Assisting lecture Wissenschaftliches Rechnen und Anwendungen in der Strömungsdynamik, SS 2006
Assisting lecture Mustererkennung II, SS 2002
Assisting lecture Algorithmen zur digitalen Bildverarbeitung, SS 2000
Assisting lecture Grundlagen der Bilderzeugung und Bildanalyse, WS 00/01, WS 01/02, WS 02/03
Teaching course Introduction into MATLAB, Sommercampus 2004
Teaching course Scientific Computing in C, WS 97/98
Seminars
Hauptseminar Hierarchische Lösungsstrategien, SS 2009
Oberseminar Angewandte Mathematik, Universitat Münster, WS 07/08, SS 2008, WS 08/09
Modellierung und Simulation , WS 08/09
Kernel Methods , WS 08/09
Effiziente numerische Verfahren und Modellreduktion , SS 2008
Mustererkennung mit Support-Vektor-Maschinen (SVM), WS 01/02, WS 02/03
Competitions
Mustererkennung mit Support-Vektor-Maschinen, WS 01/02, WS 02/03
Projects
Coordinating and assisting Softwarepraktikum SS 2001
Lab-Sessions
Teaching Praktikum Numerik für Partielle Differentialgleichungen I WS 08/09
Teaching Praktikum Wissenschaftliches Rechnen WS 07/08, SS 2008
Assisting Bildverarbeitungspraktikum II SS 2003, SS 2004
See the teaching page.
Past Semester WS 2010/2011
Lecture Diskrete Strukturen
Seminar Angewandte Mathematik
Lab Computerpraktikum
SIMTECH-Netzwerk-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Past Semester SS 2010
Lecture Reduzierte-Basis-Methoden
Proseminar Numerik
SIMTECH-Netzwerk-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Past WS 2009/2010
Workshop at Fraunhofer Talentschool 2010, 12.-14.3.2010
Angewandte Mathematik: Modellierung und Simulation in Naturwissenschaften und Technik
Lecture Modellreduktion
Computerpraktikum Wissenschaftliches Rechnen
SIMTECH-Seminar Model Reduction
Institutsseminar Angewandte Analysis und Numerische Simulation
Oberseminar Angewandte Mathematik
Lecturer Position
Teaching course Digitale Bildverarbeitung, WS 05/06, SS 2006, WS 06/07, SS 2007, WS 07/08, SS 2008 at the University of Applied Sciences Offenburg, Germany
Lectures
Lecture Einführung in die Modellreduktion, SS 2009
Tutorial Kernel Methods at IFCS@GFKL2009
Lecture Modellierung und Simulation von Straßenverkehr, Mathetage, University of Münster, 5.9.2008.
Assisting lecture Einführung in die Numerische Mathematik, WS 07/08
Assisting lecture Wissenschaftliches Rechnen und Anwendungen in der Strömungsdynamik, SS 2006
Assisting lecture Mustererkennung II, SS 2002
Assisting lecture Algorithmen zur digitalen Bildverarbeitung, SS 2000
Assisting lecture Grundlagen der Bilderzeugung und Bildanalyse, WS 00/01, WS 01/02, WS 02/03
Teaching course Introduction into MATLAB, Sommercampus 2004
Teaching course Scientific Computing in C, WS 97/98
Seminars
Hauptseminar Hierarchische Lösungsstrategien, SS 2009
Oberseminar Angewandte Mathematik, Universitat Münster, WS 07/08, SS 2008, WS 08/09
Modellierung und Simulation , WS 08/09
Kernel Methods , WS 08/09
Effiziente numerische Verfahren und Modellreduktion , SS 2008
Mustererkennung mit Support-Vektor-Maschinen (SVM), WS 01/02, WS 02/03
Competitions
Mustererkennung mit Support-Vektor-Maschinen, WS 01/02, WS 02/03
Projects
Coordinating and assisting Softwarepraktikum SS 2001
Lab-Sessions
Teaching Praktikum Numerik für Partielle Differentialgleichungen I WS 08/09
Teaching Praktikum Wissenschaftliches Rechnen WS 07/08, SS 2008
Assisting Bildverarbeitungspraktikum II SS 2003, SS 2004
Talks
16.11.2012
Einführung in RB-Methoden für instationäre Probleme,
Technische Universität München
16.11.2012
Effiziente und gesicherte numerische Simulation durch Modellreduktion,
Universität Bonn
03.10.2012
The POD-Greedy Method: Convergence Rates, Extensions and Applications,
MoRePaS-II,Reisensburg, Günzburg
25.09.2012
Reduzierte Basis Methoden für parametrisierte partielle Differentialgleichungen,
Universität Siegen
02.07.2012
The POD-Greedy Method: Convergence Rates and Applications,
AIMS Conference,Orlando
16.05.2012
Reduzierte-Basis-Methoden für Nichtlineare Probleme,
Mathematisches Kolloquium
08.05.2012
Kernel-based Model Order Reduction for Nonlinear Parametrized Problems,
Workshop on Nonlinear MOR, Schloss Ringberg, Tegernsee
4.5.2012
Modellreduktion und Maschinelles Lernen zur Prädiktion,
Hochschule Offenburg
26.3.2012
Efficient Model Reduction of Evolution Problems with Reduced Basis Methods,
DLR Braunschweig
28.2.2012
Kernel Methods for Model Order Reduction of Nonlinear Parametrized Dynamical Systems,
Control Theory Workshop, Oberwolfach
17.2.2012
Online Reduced Basis Construction for Model Reduction of Parametrized Evolution Systems.,
MATHMOD 2012, Vienna
13.2.2012
Data-based Modelling and Model Reduction for Scientific Computing,
Wir-BaWü Meeting, Karlsruhe
16.12.2011
Reduced Basis Surrogate Models for Parameter Optimization of Evolution Problems,
Numerical Analysis Seminar, Basel
8.12.2011
Reduced Basis Surrogate Models for Parameter Optimization,
IGPM Seminar, Aachen
16.11.2011
Efficient Model Reduction of Evolution Problems with Reduced Basis Methods,
Workshop RB/POD/PGD Model Reduction Techniques: A Breakthrough in Computational Engineering?, Cachan
7.11.2011
Reduced Basis Surrogate Models for Parameter Optimization,
AG Numerik Seminar, Konstanz
28.10.2011
Empirical Operator Interpolation.,
RB-Summerschool, Günzburg
6.9.2011
A Reduced Basis Method for Parametrized Variational Inequalities,
ENUMATH 2011, Leicester, UK
24.6.2011
Adaptive Basis Generation in RB-Methods for Time Dependent Problems,
Workshop RB-Methods for high-dimensional problems, Paris
26.1.2011
Adaptive Basis Generation in Reduced Basis Methods for Parametrized Evolution Equations,
Workshop on Model Order Reduction in Optimization and Control with PDEs (MOR 2011), Berlin
8.12.2010
A Reduced Basis Method for Variational Inequalities,
Workshop on Reduced Basis Methods, Ulm
9.11.2010
Hierarchical Models for Efficient Numerical Simulation and Prediction,
Model Reduction and Machine Learning SimTech Colloquium, Stuttgart
27.7.2010
Kernel Discriminant Analysis for Positive Definite and Indefinite Kernels,
Invited COMPSTAT 2010, Paris
22.6.2010
RBmatlab: A Library for Reduced Basis Methods,
MATLAB-AG, SimTech-MOR-Seminar, Stuttgart
17.5.2010
Model Reduction of Implicit and Explicit Parametrized Nonlinear Evolution Schemes by Empirical Operator Interpolation,
ECCM 2010, Paris
22.2.2010
RBmatlab: Reduced Basis Methods for Parametrized Evolution Problems,
SimTech Multiscale Seminar, Stuttgart
6.11.2009
Reduced Basis Methods for Parametrized Evolution Problems,
Forschungsseminar Scientific Computing, Chemnitz
24.9.2009
Efficient A-Posteriori Error Estimation for Parametrized reduced Dynamical Systems,
VDI-VDI FA 1.30 Workshop, Salzburg
17.9.2009
Basis Generation by Adaptive Parameter Grids,
MoRePaS 09, Münster
26.8.2009
Reduced Basis Methods for Linear and Nonlinear Finite Volume Schemes,
IACS Seminar, EPFL Lausanne, Switzerland
22.6.2009
Reduced Basis Methods for Linear and Nonlinear Finite Volume Schemes,
ICOSAHOM 2009, Trondheim, Norway
14.5.2009
Reduced Basis Methods for Parametrized Evolution Problems,
IANS Seminar, Stuttgart
13.2.2009
Efficient Reduced Models for Parametrized Dynamical Systems by Offline/Online Decomposition,
Invited MATHMOD 2009
12.2.2009
Space-Adaptive Reduced Basis Simulation for Time-Dependent Problems,
MATHMOD 2009
6.1.2009
Reduzierte Basis Methoden zur Modellreduktion von Parametrisierten Partiellen Differentialgleichungen,
CeNoS Kolloquium Nonlinear Science, Münster
10.12.2008
Indefinite Kernel Fisher Discriminant,
ICPR 2008, Tampa, Florida
12.11.2008
Model Reduction of Parametrized Evolution Problems by Reduced Basis Methods,
Regelungstechnisches Seminar, TU München
16.7.2008
Classification with Regularized Kernel Mahalanobis Distances,
GfKl 2008, Helmut Schmidt Universität Hamburg
27.5.2008
Reduced Basis Methods for Parametrized Evolution Problems,
JP-Conference, Universität Stuttgart
15.1.2008
Reduced Basis Methods for Model Reduction of Parametrized Evolution Schemes,
Oberseminar Angewandte Mathematik, Universität Münster
24.10.2007
Basis Construction for Reduced Basis Methods with Adaptive Parameter Grids,
International Conference on Adaptive Modeling and Simulation ADMOS 2007, Göteborg
24.09.2007
Reduced Basis Method for Evolution Schemes with Parameter Dependent Explicit Operators,
Chemnitz FEM Symposium
20.4.2007
Reduced Basis Method for Finite Volume Schemes,
Aerospace Computational Design Laboratory Seminar, Massachusetts Institute of Technology
20.-21.11.2006
Combining Kernels and Distances,
Invited Kernel Combining Workshop, University of Delft
18.-20.9.2006
Reduced Basis Method for Parametrized Evolution Equations,
PEMSIM 2006, WIAS Berlin
23.6.2006
Transformation Knowledge in Pattern Analysis with Kernel Methods,
FDM-Seminar, University of Freiburg
22.4.2005
Invariance in Kernel Methods - Distance and Integration Kernels,
Departement Informatik, University of Basel
15.4.2005
Invariance in Pattern Analysis with Kernel Methods,
FhG-IPSI, Darmstadt
16.-18.3.2005
Invariance in Kernel Methods - Distance and Integration Kernels,
Machine Learning, Support Vector Machines, and Large Scale Optimization Workshop, Schloss Thurnau
21.7.2003
Feature Space Interpretation of SVM with Indefinite Kernels,
Oberseminar Bildverarbeitung, Computersehen und Computergraphik, University of Freiburg
22.1.2003
Invariance Knowledge in Kernel Functions,
MPI for Biological Kybernetics
7.-9.10.2002
Invariance Knowledge in Kernel Functions,
Schloss Dagstuhl
4.-5.12.2000
Convergence of a Staggered Lax-Friedrichs-Scheme on Unstructured 2D Grids,
Workshop on Finite-Volume Methods, Unversity of Freiburg
20.-24.3.2000
h-p Multiresolution Visualization of Adaptive Simulations,
International Springschool on Visualization, Bonn-Röttgen
1999
Konvergenz eines Staggered-Lax-Friedrichs-Verfahrens auf unstrukturierten 2D Gittern,
Oberseminar Angewandte Mathematik, University of Freiburg
Further information
Bibliometrical Data
Citations: 2448 (Google Scholar)
h-index: 23 (Google Scholar)
i10: 45 (Google Scholar)
Publications: 119 (Google Scholar), 29 (DBLP.uni-trier.de), 36 (Zentralblatt MATH)
Erdös Number: 5 (Alfred Schmidt, Zhi Ming Chen, Qiang Du, Vance Faber, Paul Erdös)
Funded Projects
Principal Investigator in a project funded by the Baden Württemberg
Stiftung gGmbH, MWK-BW (Juniorprofessorenprogramm), RB-Methoden für Heterogene Gebietszerlegung,
2012-2015.
Principal Investigator in a project funded by the Baden Württemberg Stiftung gGmbH, MWK-BW (Juniorprofessorenprogramm), Maschinelles Lernen zur Simulationsbasierten Modellreduktion, 2010-2013.
Principal Investigator in a project funded by the DFG within the SimTech Cluster of Excellence (JP-Anschubprojekt), KerMor: Kernel Methods for Model Order Reduction of Biochemical Systems. , 2010-2012.
Principal Investigator in a project funded by the DFG within the SimTech Cluster of Excellence, RBEvolOpt: Reduced Basis Modelling of Higher-Order Evolution Systems and Application in Optimisation, 2009-2014.
Principal Investigator (with M. Ohlberger) in a project funded by the DFG, Reduzierte Basis Methoden zur Modellreduktion für Nichtlineare Parametrisierte Evolutionsgleichungen, 2009-2012.
Organizer (with M. Ohlberger, T. Tonn and K. Urban) in a workshop funded by the DFG, MoRePaS 09, Model Reduction of Parametrized Systems, Unversity of Münster, September 16-18, 2009.
Principal Investigator in a project funded by the Landesstiftung Baden-Württemberg gGmbH, Modellreduktion zur Simulation von Transportprozessen und Anwendungen in Brennstoffzellen, 2007-2009.
Principal Investigator (with E. Pekalska) in a project funded by the DAAD, Indefinite Kernel Methods and Learning in General Proximity Spaces , 2007-2008.
In charge of BMBF sub-project for Modellbasiertes Design von Brennstoffzellen und Brennstoffzellensystemen: PEMDesign, 2005-2008.
In charge of BMBF sub-project for ULI, Universitärer Lehrverbund Informatik, 2001-2003.
Principal Investigator in a project funded by the Baden Württemberg Stiftung gGmbH, MWK-BW (Juniorprofessorenprogramm), Maschinelles Lernen zur Simulationsbasierten Modellreduktion, 2010-2013.
Principal Investigator in a project funded by the DFG within the SimTech Cluster of Excellence (JP-Anschubprojekt), KerMor: Kernel Methods for Model Order Reduction of Biochemical Systems. , 2010-2012.
Principal Investigator in a project funded by the DFG within the SimTech Cluster of Excellence, RBEvolOpt: Reduced Basis Modelling of Higher-Order Evolution Systems and Application in Optimisation, 2009-2014.
Principal Investigator (with M. Ohlberger) in a project funded by the DFG, Reduzierte Basis Methoden zur Modellreduktion für Nichtlineare Parametrisierte Evolutionsgleichungen, 2009-2012.
Organizer (with M. Ohlberger, T. Tonn and K. Urban) in a workshop funded by the DFG, MoRePaS 09, Model Reduction of Parametrized Systems, Unversity of Münster, September 16-18, 2009.
Principal Investigator in a project funded by the Landesstiftung Baden-Württemberg gGmbH, Modellreduktion zur Simulation von Transportprozessen und Anwendungen in Brennstoffzellen, 2007-2009.
Principal Investigator (with E. Pekalska) in a project funded by the DAAD, Indefinite Kernel Methods and Learning in General Proximity Spaces , 2007-2008.
In charge of BMBF sub-project for Modellbasiertes Design von Brennstoffzellen und Brennstoffzellensystemen: PEMDesign, 2005-2008.
In charge of BMBF sub-project for ULI, Universitärer Lehrverbund Informatik, 2001-2003.
Awards
2012: Teaching Award "Beste Vertiefungsvorlesung" of the Fachschaft Mathematik of the University of Stuttgart for the lecture "Reduced Basis Methods".
2009: Best Paper Award for the contribution: Haasdonk, B., Pekalska, E., Classification with Kernel Mahalanobis Distances. Proc. of 32nd. GfKl Conference, Advances in Data Analysis, Data Handling and Business Intelligence, 2008.
2012: Teaching Award "Beste Vertiefungsvorlesung" of the Fachschaft Mathematik of the University of Stuttgart for the lecture "Reduced Basis Methods".
2009: Best Paper Award for the contribution: Haasdonk, B., Pekalska, E., Classification with Kernel Mahalanobis Distances. Proc. of 32nd. GfKl Conference, Advances in Data Analysis, Data Handling and Business Intelligence, 2008.
2008: Participation in the Awarded Exhibition
Hightech
Underground 2008
2007: DAAD-ARC research grant
2006: Admittance to the Eliteprogramm für Postdoktorandinnen und Postdoktoranden of the Landesstiftung Baden-Württemberg gGmbH
2004: Prize in SAS Mining Challenge 2003
2002: Best Paper Presentation Award for the contribution: Bahlmann, C., Haasdonk, B., Burkhardt, H., On-Line Handwriting Recognition with Support Vector Machines - A Kernel Approach. IWFHR-8, 2002. (.ps, .pdf)
2000: Förderpreis 2000 des Verbands der Freunde der Universität Freiburg for the best graduation at the Institute of Mathematics.
Professional Activities
Scientific Organizations
DMV, German Mathematicians Society
DAGM, German Pattern Recognition Society
IAPR, International Association for Pattern Recognition
DHV, German Association of University Professors and Lecturers
WiR-Ba-Wü, Research network for scientific computing in Baden-Württemberg.
DMV, German Mathematicians Society
DAGM, German Pattern Recognition Society
IAPR, International Association for Pattern Recognition
DHV, German Association of University Professors and Lecturers
WiR-Ba-Wü, Research network for scientific computing in Baden-Württemberg.
CoSiMOR, Scientific
Network on Scale Bridging simulation methods based on order-reduction and co-simulation
Research Visits
11/2013: Stanford University, California, USA
3/2011: Massachusetts Institute of Technology, Cambridge, USA
10/2009: University of Manchester, Manchester, UK.
8/2009: Ecole Polytechnique Lausanne, Lausanne, Switzerland.
8/2008: University of Manchester, Manchester, UK.
9/2007: University of Manchester, Manchester, UK.
4/2007-7/2007: Massachusetts Institute of Technology, Cambridge, USA.
4/2003: Max Planck Institute for Biological Kybernetics, Tübingen, Germany.
10/2009: University of Manchester, Manchester, UK.
8/2009: Ecole Polytechnique Lausanne, Lausanne, Switzerland.
8/2008: University of Manchester, Manchester, UK.
9/2007: University of Manchester, Manchester, UK.
4/2007-7/2007: Massachusetts Institute of Technology, Cambridge, USA.
4/2003: Max Planck Institute for Biological Kybernetics, Tübingen, Germany.
Workshop/Conference Organization
GAMM 2013, Minisymposium on "Model Order Reduction" at the 89th Annual GAMM Conference
Novi Sad, Serbia, March 18-22, 2013.
SIAM CSE 2013, Minisymposium on "Data-based and Nonlinear Model Order
Reduction", Boston, MA, USA, February 25 - March 1, 2013
IANS Miniworkshop on "Minimum Energy Problems"
Stuttgart, Germany, August 17-18, 2012.
MATHMOD 2012, Minisymposium on "Model Order Reduction" at the 7th Vienna International Conference on Mathematical Modelling
Vienna, Austria, February 15-17, 2012.
CEMRACS 2011, SimTech Workshop on "Current Trends in Computational Fluid Mechanics"
Marseille, France, August 22-24, 2011.
SIAM CSE 2011, Mini-Symposium on "Model Reduction of Nonlinear and Parametrized Problems"
Reno, Nevada, February 28-March 4, 2011.
Workshop on Reduced Basis Methods,
Ulm, December 7-8, 2010.
ECCOMAS CFD 2010, Mini-Symposium on "Model Reduction in Computational Fluid Dynamics"
Lisbon, June 14-17, 2010.
MoRePaS 09, Workshop on Model Reduction of Parametrized Systems
Münster, September 16-18, 2009. (successful DFG funding)
PEMSIM2006, Workshop on Modelling and Simulation of PEM Fuel Cells
Berlin, September 18-20, 2006
Journal Referee Activities
SISC, SIAM Journal on Scientific Computing
SINUM, SIAM Journal on Numerical Analysis
JUQ, SIAM/ASA Journal on
Uncertainty Quantification
ESAIM M2AN, Mathematical Modelling and Numerical Analysis
CRAS, Comptes Rendus de l'Acadämie des Sciences
MCMDS, Mathematical and Computer Modelling of Dynamical Systems
ZAMM, Journal of Applied Mathematics and Mechanics
ESAIM M2AN, Mathematical Modelling and Numerical Analysis
CRAS, Comptes Rendus de l'Acadämie des Sciences
MCMDS, Mathematical and Computer Modelling of Dynamical Systems
ZAMM, Journal of Applied Mathematics and Mechanics
CMAME, Computer Methods in Applied Mechanics and Engineering
IJMM, International Journal of Modern Mathematics
IEEE TPAMI, Transactions on Pattern Analysis and Machine Intelligence
IEEE TIP, Transactions on Image Processing
IEEE TNN, Transactions on Neural Networks
ACM TOIS, Transactions on Information Systems
IEEE TPDS, Transactions on Parallel and Distributed Systems
JMLR, Journal of Machine Learning Research
Neural Computation
Neurocomputing
Pattern Recognition
Pattern Recognition Letters
Pattern Analysis and Applications
IJPRAI, International Journal of Pattern Recognition and Artificial Intelligence
Information Fusion
Signal Processing
IJNS, International Journal of Neural Systems
EJOR, European Journal of Operational Research
SMCB, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SMCC, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
TFS, IEEE Transactions on Fuzzy Systems
CES, Chemical Engineering Science
IJMM, International Journal of Modern Mathematics
IEEE TPAMI, Transactions on Pattern Analysis and Machine Intelligence
IEEE TIP, Transactions on Image Processing
IEEE TNN, Transactions on Neural Networks
ACM TOIS, Transactions on Information Systems
IEEE TPDS, Transactions on Parallel and Distributed Systems
JMLR, Journal of Machine Learning Research
Neural Computation
Neurocomputing
Pattern Recognition
Pattern Recognition Letters
Pattern Analysis and Applications
IJPRAI, International Journal of Pattern Recognition and Artificial Intelligence
Information Fusion
Signal Processing
IJNS, International Journal of Neural Systems
EJOR, European Journal of Operational Research
SMCB, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
SMCC, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
TFS, IEEE Transactions on Fuzzy Systems
CES, Chemical Engineering Science
Software
Software Packages
RBMatlab: MATLAB toolbox for Reduced Basis Methods and Model Order Reduction
DUNE, DUNE-FEM, DUNE-RB: Distributed and Unified Numerics Environment
KerMet-Tools: MATLAB toolbox for invariant kernel experiments in pattern analysis.
Presto-Box: Scilab toolbox with basic pattern recognition algorithms.
libsvmTL: C++ SVM template library based on libsvm
VisAmp: plattform independent, visually controlled mp3-player
GRAPE: GRAphical Programming Environment for mathematical visualization
Datasets
Distance Matrices: Small collection of proximity data used in the DAGM2004 paper.
RBMatlab: MATLAB toolbox for Reduced Basis Methods and Model Order Reduction
DUNE, DUNE-FEM, DUNE-RB: Distributed and Unified Numerics Environment
KerMet-Tools: MATLAB toolbox for invariant kernel experiments in pattern analysis.
Presto-Box: Scilab toolbox with basic pattern recognition algorithms.
libsvmTL: C++ SVM template library based on libsvm
VisAmp: plattform independent, visually controlled mp3-player
GRAPE: GRAphical Programming Environment for mathematical visualization
Datasets
Distance Matrices: Small collection of proximity data used in the DAGM2004 paper.