60 citations · 64 across the 8 of their papers we have counts for
4 papers · 1 filter
Nearest Neighbor Sampling for Covariate Shift Adaptation
François Portier, Lionel Truquet, Ikko Yamane
Many existing covariate shift adaptation methods estimate sample weights given to loss values to mitigate the gap between the source and the target distribution. However, estimatin…
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian Yger +1
Ordinary supervised learning is useful when we have paired training data of input and output . However, such paired data can be difficult to collect in practice. In this pap…
Uplift Modeling from Separate Labels
Ikko Yamane, Florian Yger, Jamal Atif +1
Uplift modeling is aimed at estimating the incremental impact of an action on an individual's behavior, which is useful in various application domains such as targeted marketing (a…
Regularized Multi-Task Learning for Multi-Dimensional Log-Density Gradient Estimation
Ikko Yamane, Hiroaki Sasaki, Masashi Sugiyama
Log-density gradient estimation is a fundamental statistical problem and possesses various practical applications such as clustering and measuring non-Gaussianity. A naive two-step…