- Oggetto:
Introduction to Kernel Methods and their Applications
- Oggetto:
Introduction to Kernel Methods and their Applications
- Oggetto:
Academic year 2019/2020
- Teaching staff
- Prof. Roberto Cavoretto (Lecturer)
Prof. Alessandra De Rossi (Lecturer) - Type
- Basic
- Credits/Recognition
- 30 hours
- Course disciplinary sector (SSD)
- MAT/08 - analisi numerica
- Delivery
- Formal authority
- Language
- English
- Attendance
- Obligatory
- Oggetto:
Sommario del corso
- Oggetto:
Program
• Scattered data interpolation.
• Kernel methods and radial basis functions.
• Partition of unity methods.
• Generation of scattered data sets on the plane and on the sphere.
• Spherical interpolation.
• Application of radial basis functions in image processing.
• Fast algorithms for interpolation of large scattered data sets.
• Numerical linear algebra methods in scattered data approximation.Suggested readings and bibliography
- Oggetto:
• M. D. Buhmann, Radial Basis Functions: Theory and Implementation, Cambridge Monogr. Appl. Comput. Math., vol. 12, Cambridge Univ. Press, Cambridge, 2003.
• G. E. Fasshauer, Meshfree Approximation Methods with Matlab, World Scientific Publishers, Singapore, 2007.
• G. Fasshauer, M. McCourt, Kernel-based Approximation Methods using Matlab, World Scientific, Singapore, 2015.
• J. Modersitzki, Numerical Methods for Image Registration, Oxford Univ. Press, New York, 2004.
• K. Rohr, Landmark-Based Image Analysis, Using Geometric and Intensity Models, Kluwer Academic Publishers, Norwell, MA, 2001.
• H. Wendland, Scattered Data Approximation, Cambridge Monogr. Appl. Comput. Math., vol. 17, Cambridge Univ. Press, Cambridge, 2005.- Oggetto:
Note
Duration and period: 30 hours (March - May 2020)
Contact the teachers for class schedule by January 31, 2020
- Oggetto:
