We have two goals:
- Machine learning for science: Develop machine learning methods that help scientists finding new scientific discoveries.
- Machine learning: Develop fundamental machine learning algorithms.
- High-dimensional nonlinear feature selection
- Matrix completion
Selective Inference for Kernels
- Selective Independence test
- Selective two-sample test
- Selective goodness of fit test
- OT for tree-structured data
- OT for high-dimensional data
- OT based Semantic correspondence