Our team, deep learning theory team, is studying various kinds of learning systems including deep learning from theoretical viewpoints. We enrich our understandings of complex learning systems, and leverage the insights to construct new machine learning techniques and apply them. Especially, machine learning should deal with high dimensional and complicated data, and thus we are studying deep learning and structured sparse learning as methods to deal with such complicated data. Moreover, we are also developing efficient optimization algorithms for large and complicated machine learning problems based on such techniques as stochastic optimization.
Efficient optimization algorithm for large dataset
High dimensional statistics