Yukihiro Tagami — accepted AI-conference papers

2016

Gaussian process nonparametric tensor estimator and its minimax optimality

Heishiro Kanagawa, Taiji Suzuki, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami

ICML 2016poster

We investigate the statistical efficiency of a nonparametric Gaussian process method for a nonlinear tensor estimation problem. Low-rank tensor estimation has been used as a method to learn higher order relations among several data sources in a wide range of applications, such as multi-task learning…

Cited by 27 Source ↗PDF ↗Scholar ↗

2016

Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning

Taiji Suzuki, Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu, Yukihiro Tagami

NeurIPS 2016poster

We investigate the statistical performance and computational efficiency of the alternating minimization procedure for nonparametric tensor learning. Tensor modeling has been widely used for capturing the higher order relations between multimodal data sources. In addition to a linear model, a nonl…

Cited by 23 Source ↗PDF ↗Scholar ↗