4 papers
Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite
Yushi Hirose, Hiroo Irobe, Takafumi Kanamori
Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated. While PNU learning, a risk rewriting meth…
Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence
Takafumi Kanamori, Yushi Hirose, Shohei Yamamoto
We study component recovery and mixing-matrix estimation from unlabeled finite mixtures whose observable distributions share the same latent components but have unknown mixing weig…
Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
Yushi Hirose, Akito Narahara, Takafumi Kanamori
Mixture proportion estimation (MPE) aims to estimate class priors from unlabeled data. This task is a critical component in weakly supervised learning, such as PU learning, learnin…
Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding
Yushi Hirose, Masashi Shimbo, Taro Watanabe
For knowledge graph completion, two major types of prediction models exist: one based on graph embeddings, and the other based on relation path rule induction. They have different…