ISM, Japan
Prof Kenji Fukumizu, ISM Japan
Title: TBC
Background:
I am interested in theory and practice of learning with complex and structured data, and working from the viewpoints of statistics, mathematics and machine learning. More specific research projects include the following topics;
- Kernel method (data analysis with positive definite kernels): Nonparametric data analysis with positive definite kernels and reproducing kernel Hilbert spaces. Expressing probabilistic knowledge using embedding of data in reproducing kernel Hilbert spaces, and its applications to extracting dependence, conditional dependence structure among variables. Inference of causal networks with these methods.
- Geometry of algorithms on graphs: Analysis of algorithms on graphs, such as belief propagation, with graph geometry, graph polynomial and so on.
- Singular statistical models: Statistical inference with parametric models with singularities. Nonstandard asymptotic behavior of the estimator around sigularities.