About me


Research interests

My central focus of research is in theoretical understanding of statistical machine learning, particularly from the following perspectives.

  1. Learning theory of loss functions, through which I like to study robustness to adversarial attacks (COLT2020) and class imbalance (AISTATS2020, AISTATS2021).
  2. Evaluation metrics of predictions and representations. Recently, I am interested in how it is possible to learn good representations via similarity in light of a downstream task (ICML2018, preprint).

I am glad to have discussions with those who have common interests! You may have a look at the slides of my past talks such as this to see my tastes.


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