4 papers
Testing Goodness of Fit of Conditional Density Models with Kernels
Wittawat Jitkrittum, Heishiro Kanagawa, Bernhard Schölkopf
We propose two nonparametric statistical tests of goodness of fit for conditional distributions: given a conditional probability density function and a joint sample, decid…
Amortised Learning by Wake-Sleep
Li K. Wenliang, Theodore Moskovitz, Heishiro Kanagawa +1
Models that employ latent variables to capture structure in observed data lie at the heart of many current unsupervised learning algorithms, but exact maximum-likelihood learning f…
Informative Features for Model Comparison
Wittawat Jitkrittum, Heishiro Kanagawa, Patsorn Sangkloy +3
Given two candidate models, and a set of target observations, we address the problem of measuring the relative goodness of fit of the two models. We propose two new statistical tes…
Cross-domain Recommendation via Deep Domain Adaptation
Heishiro Kanagawa, Hayato Kobayashi, Nobuyuki Shimizu +2
The behavior of users in certain services could be a clue that can be used to infer their preferences and may be used to make recommendations for other services they have never use…