Search Results for author: Yoshihiro Yamanishi

Found 3 papers, 0 papers with code

Dual Convolutional Neural Network for Graph of Graphs Link Prediction

no code implementations4 Oct 2018 Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima

Graphs are general and powerful data representations which can model complex real-world phenomena, ranging from chemical compounds to social networks; however, effective feature extraction from graphs is not a trivial task, and much work has been done in the field of machine learning and data mining.

Link Prediction

Space-efficient Feature Maps for String Alignment Kernels

no code implementations18 Feb 2018 Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh

We present novel space-efficient feature maps (SFMs) of RFFs for a space reduction from O(dD) of the original FMs to O(d) of SFMs with a theoretical guarantee with respect to concentration bounds.

Supervised Bipartite Graph Inference

no code implementations NeurIPS 2008 Yoshihiro Yamanishi

We formulate the problem of bipartite graph inference as a supervised learning problem, and propose a new method to solve it from the viewpoint of distance metric learning.

Metric Learning

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