31 citations · 71 across the 8 of their papers we have counts for
6 papers · 1 filter
Relative Density-Ratio Estimation for Robust Distribution Comparison
Makoto Yamada, Taiji Suzuki, Takafumi Kanamori +2
Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully app…
Least-Squares Independence Regression for Non-Linear Causal Inference under Non-Gaussian Noise
Makoto Yamada, Masashi Sugiyama, Jun Sese
The discovery of non-linear causal relationship under additive non-Gaussian noise models has attracted considerable attention recently because of their high flexibility. In this pa…
Sufficient Component Analysis for Supervised Dimension Reduction
Makoto Yamada, Gang Niu, Jun Takagi +1
The purpose of sufficient dimension reduction (SDR) is to find the low-dimensional subspace of input features that is sufficient for predicting output values. In this paper, we pro…
Sharp Convergence Rate and Support Consistency of Multiple Kernel Learning with Sparse and Dense Regularization
Taiji Suzuki, Ryota Tomioka, Masashi Sugiyama
We theoretically investigate the convergence rate and support consistency (i.e., correctly identifying the subset of non-zero coefficients in the large sample limit) of multiple ke…
Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization
Taiji Suzuki, Ryota Tomioka, Masashi Sugiyama
We investigate the learning rate of multiple kernel leaning (MKL) with elastic-net regularization, which consists of an -regularizer for inducing the sparsity and an $\ell_…
Cross-Domain Object Matching with Model Selection
Makoto Yamada, Masashi Sugiyama
The goal of cross-domain object matching (CDOM) is to find correspondence between two sets of objects in different domains in an unsupervised way. Photo album summarization is a ty…