Poignard, Benjamin
ポワニャール ベンジャミン
Poignard, Benjamin
Faculty of Science and Technology Department of Mathematics/Associate ProfessorBasic Information
Specialty
Statistics, Econometrics, Multivariate time series, Sparse modeling, Machine learning
Paper Review Qualification
Thesis Guide Qualification in the Graduate School of Science and Technology : Master/Doctor
Biography
Research experience
RIKEN AIP Continuous optimization team Visiting scientist
RIKEN AIP High-dimensional statistical modeling unit
The University of Osaka Graduate School of Economics
Research
Reseach overview
The research is dedicated to the sparse statistical modeling for multivariate random models. It aims to solve the curse of dimensionality problem, that is the explosive number of parameters, inherent to most multivariate models by fostering parsimony among the parameters. The following points are considered: - the specification of relevant sparsity-based techniques; - the theoretical analysis of the sparsity-based estimators (asymptotic properties, finite sample); - the implementation of efficient optimization procedures.
Research Interests
- Sparsity
- Time series
- Asymptotic theory
- High-dimensional statistics
Research areas
Statistical science / Asymptotic theory; Sparsity; Time series