Seminar for Applied Mathematics

Report from Dagstuhl Seminar 17292 Topology , Computation and

This report documents the program and the outcomes of Dagstuhl Seminar 17292 “Topology, Computation and Data Analysis”. This seminar was the first of its kind in bringing together researchers with mathematical and computational backgrounds in addressing emerging directions within computational topology for data analysis in practice. The seminar connected pure and applied mathematicians, with th...

Probabilistic Methods in the Design and Analysis of Algorithms (Dagstuhl Seminar 17141)

This report documents the program and the outcomes of Dagstuhl Seminar 17141 “Probabilistic Methods in the Design and Analysis of Algorithms”. Probabilistic methods play a central role in theoretical computer science. They are a powerful and widely applied tool used, for example, for designing efficient randomized algorithms and for establishing various lower bounds in complexity theory. They a...

CJS 2008 in Miyazaki Program and Abstracts of Czech - Japanese Seminar in Applied Mathematics 2008

Mathematical and Computational Foundations of Learning

Machine learning has become a core field in computer science. Over the last decade the statistical machine learning approach has been successfully applied in many areas such as bioinformatics, computer vision, robotics and information retrieval. The main reasons for the success of machine learning are its strong theoretical foundations and its multidisciplinary approach integrating aspects of c...

Probabilistic Methods in the Design and Analysis of Algorithms, 23.09. - 28.09.2007

This report documents the program and the outcomes of Dagstuhl Seminar 17141 “Probabilistic Methods in the Design and Analysis of Algorithms”. Probabilistic methods play a central role in theoretical computer science. They are a powerful and widely applied tool used, for example, for designing efficient randomized algorithms and for establishing various lower bounds in complexity theory. They a...