11 citations · 19 across the 7 of their papers we have counts for
13 papers
Generalization Error Bound for Hyperbolic Ordinal Embedding
Atsushi Suzuki, Atsushi Nitanda, Jing Wang +3
Hyperbolic ordinal embedding (HOE) represents entities as points in hyperbolic space so that they agree as well as possible with given constraints in the form of entity i is more s…
Detecting Hierarchical Changes in Latent Variable Models
Shintaro Fukushima, Kenji Yamanishi
This paper addresses the issue of detecting hierarchical changes in latent variable models (HCDL) from data streams. There are three different levels of changes for latent variable…
Word2vec Skip-gram Dimensionality Selection via Sequential Normalized Maximum Likelihood
Pham Thuc Hung, Kenji Yamanishi
In this paper, we propose a novel information criteria-based approach to select the dimensionality of the word2vec Skip-gram (SG). From the perspective of the probability theory, S…
A Novel Global Spatial Attention Mechanism in Convolutional Neural Network for Medical Image Classification
Linchuan Xu, Jun Huang, Atsushi Nitanda +2
Spatial attention has been introduced to convolutional neural networks (CNNs) for improving both their performance and interpretability in visual tasks including image classificati…
Mixture Complexity and Its Application to Gradual Clustering Change Detection
Shunki Kyoya, Kenji Yamanishi
In model-based clustering using finite mixture models, it is a significant challenge to determine the number of clusters (cluster size). It used to be equal to the number of mixtur…
Detecting Change Signs with Differential MDL Change Statistics for COVID-19 Pandemic Analysis
Kenji Yamanishi, Linchuan Xu, Ryo Yuki +2
We are concerned with the issue of detecting changes and their signs from a data stream. For example, when given time series of COVID-19 cases in a region, we may raise early warni…