3 citations · 4 across the 4 of their papers we have counts for
4 papers
Accelerating spherical K-means clustering for large-scale sparse document data
Kazuo Aoyama, Kazumi Saito
This paper presents an accelerated spherical K-means clustering algorithm for large-scale and high-dimensional sparse document data sets. We design an algorithm working in an archi…
Acceleration Method for Learning Fine-Layered Optical Neural Networks
Kazuo Aoyama, Hiroshi Sawada
An optical neural network (ONN) is a promising system due to its high-speed and low-power operation. Its linear unit performs a multiplication of an input vector and a weight matri…
Structured Inverted-File k-Means Clustering for High-Dimensional Sparse Data
Kazuo Aoyama, Kazumi Saito
This paper presents an architecture-friendly k-means clustering algorithm called SIVF for a large-scale and high-dimensional sparse data set. Algorithm efficiency on time is often…
Inverted-File k-Means Clustering: Performance Analysis
Kazuo Aoyama, Kazumi Saito, Tetsuo Ikeda
This paper presents an inverted-file k-means clustering algorithm (IVF) suitable for a large-scale sparse data set with potentially numerous classes. Given such a data set, IVF eff…