While highly expressive parametric models including deep neural networks...
Density power divergence (DPD) [Basu et al. (1998), Biometrika], which i...
A dynamical system produces a dependent multivariate sequence called
dyn...
This study proposes an interpretable neural network-based non-proportion...
In this study, we examine a clustering problem in which the covariates o...
For supervised classification problems, this paper considers estimating ...
This paper discusses the estimation of the generalization gap, the diffe...
We study a minimax risk of estimating inverse functions on a plane, whil...
This note discusses a nonparametric approach to link regression aiming a...
Multimodal relational data analysis has become of increasing importance ...
k-nearest neighbour (k-NN) is one of the simplest and most widely-used
m...
A collection of U (∈N) data vectors is called a U-tuple,
and the assoc...
We propose weighted inner product similarity (WIPS) for
neural-network b...
We propose β-graph embedding for robustly learning feature vectors from
...
We propose shifted inner-product similarity (SIPS), which is a novel yet...
The representation power of similarity functions used in neural network-...
A simple framework Probabilistic Multi-view Graph Embedding (PMvGE) is
p...