Keynote Lectures
Available Soon
Julie Dugdale, Laboratoire d'Informatique de Grenoble, France
Interpolating Multidimensional Sparse and Dense Reduced Data
Ryszard Kozera, Warsaw University of Life Sciences, Poland
Available Soon
Julie Dugdale
Laboratoire d'Informatique de Grenoble
France
http://magma.imag.fr/content/julie-dugdale
Brief Bio
Available Soon
Interpolating Multidimensional Sparse and Dense Reduced Data
Ryszard Kozera
Warsaw University of Life Sciences
Poland
![]()
Brief Bio
Prof. Ryszard KOZERA is currently a Director of The Institute of Information Technology at Warsaw University
of Life Sciences - SGGW in Poland. He obtained a Habilitation Degree (DSc) from Silesian University of
Technology (Poland) in 2006, a PhD from Flinders University of South Australia (Australia) in 1991 and a MSc
Degree from Warsaw University (Poland) in 1985. Selected previous research positions include: Assoc. Prof. at
The University of Western Australia, Perth, Australia 1991-2008 (current adjunct Assoc. Prof.) and Prof. at
Warsaw University of Technology, Poland 2009-2012. In addition, he was also awarded three times Alexander
von Humboldt Research Fellowships (Technical University of Berlin 1996-97; Christian Albrechts University of
Kiel, 2000, 2004) in Germany. His research interests are: optimization, interpolation and approximation, computer
vision and image analysis, numerical analysis, neural computation and networks, artificial intelligence, partial
differential equations and in general applied mathematics and modeling and simulation of processes in physics,
engineering, biology, medical sciences, computer science and agriculture. He published over 160 scientific papers
in international journals, research monographs and conference proceedings. He organized numerous international
conferences, workshops and sessions among all in Australia, Germany, Greece, Mexico, New Zealand and Poland.
He delivered over 70 talks and conference presentations world-wide. Prof. R. Kozera served also as co-editor of
conference proceedings, research monographs, journal, conference and book reviewer as well as he has also won
international grants and rewards. He was the assessor of the EU postdoctoral projects (Marie-Curie Fellowships).
He supervised over 85 BSc, Honours or MSc students and 4 PhD conferred students in Australia and Poland. He
delivered lectures on over 30 different topics at the undergraduate, postgraduate and PhD levels in computer
science (computer vision, artificial intelligence, neural computation) and applied mathematics (numerical
analysis, interpolation, optimization and partial differential equations). Full publication list can be found under:
https://bw.sggw.edu.pl/
Abstract
The problem of fitting a given ordered sample of data points in arbitrary Euclidean
space is discussed for both dense and sparse data. The corresponding knots are
assumed to be unknown and must first somehow be found. Various recipes
replacing the unknown knots for different interpolation schemes are addressed and
analyzed. For sparse data the latter leads to a highly non-linear multivariate
optimization task, equally non-trivial for theoretical analysis and for derivation of a
computationally efficient numerical scheme. Differtent numerical algorithms
including Leap-Frog are compared. In case of dense data the issue of convergence
of the interpolant to the unknown curve (together with the resulting order rate and
its sharpness) is discussed. Illustrative synthetic and real examples supplement the
analysis in question.