13 citations · 27 across the 7 of their papers we have counts for
14 papers
Nonparametric estimation of the preferential attachment function from one network snapshot
Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Preferential attachment is commonly invoked to explain the emergence of those heavy-tailed degree distributions characteristic of growing network representations of diverse real-wo…
Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization
Morihiro Mizutani, Akifumi Okuno, Geewook Kim +1
Multimodal relational data analysis has become of increasing importance in recent years, for exploring across different domains of data, such as images and their text tags obtained…
Extrapolation Towards Imaginary -Nearest Neighbour and Its Improved Convergence Rate
Akifumi Okuno, Hidetoshi Shimodaira
-nearest neighbour (-NN) is one of the simplest and most widely-used methods for supervised classification, that predicts a query's label by taking weighted ratio of observed…
More Powerful Selective Kernel Tests for Feature Selection
Jen Ning Lim, Makoto Yamada, Wittawat Jitkrittum +3
Refining one's hypotheses in the light of data is a common scientific practice; however, the dependency on the data introduces selection bias and can lead to specious statistical a…
Joint Estimation of the Non-parametric Transitivity and Preferential Attachment Functions in Scientific Co-authorship Networks
Masaaki Inoue, Thong Pham, Hidetoshi Shimodaira
We propose a statistical method to estimate simultaneously the non-parametric transitivity and preferential attachment functions in a growing network, in contrast to conventional m…
Hyperlink Regression via Bregman Divergence
Akifumi Okuno, Hidetoshi Shimodaira
A collection of data vectors is called a -tuple, and the association strength among the vectors of a tuple is termed as the \emph{hyperlink weight}, that…