29 citations · 49 across the 7 of their papers we have counts for
7 papers
Inferring cell-specific lncRNA regulation with single-cell RNA-sequencing data in the developing human neocortex
Meng Huang, Jiangtao Ma, Changzhou Long +3
Long non-coding RNAs (lncRNAs) are important regulators to modulate gene expression and cell proliferation in the developing human brain. Previous methods mainly use bulk lncRNA an…
Unveiling interpretable development-specific gene signatures in the developing human prefrontal cortex with ICGS
Meng Huang, Xiucai Ye, Tetsuya Sakurai
In this paper, to unveil interpretable development-specific gene signatures in human PFC, we propose a novel gene selection method, named Interpretable Causality Gene Selection (IC…
Contour Integral-based Quantum Algorithm for Estimating Matrix Eigenvalue Density
Yasunori Futamura, Xiucai Ye, Tetsuya Sakurai
The eigenvalue density of a matrix plays an important role in various types of scientific computing such as electronic-structure calculations. In this paper, we propose a quantum a…
LSEC: Large-scale spectral ensemble clustering
Hongmin Li, Xiucai Ye, Akira Imakura +1
Ensemble clustering is a fundamental problem in the machine learning field, combining multiple base clusterings into a better clustering result. However, most of the existing metho…
Divide-and-conquer based Large-Scale Spectral Clustering
Hongmin Li, Xiucai Ye, Akira Imakura +1
Spectral clustering is one of the most popular clustering methods. However, how to balance the efficiency and effectiveness of the large-scale spectral clustering with limited comp…
A Novel Sybil Attack Detection Scheme Based on Edge Computing for Mobile IoT Environment
Manli Yuan, Liwei Lin, Zhengyu Wu +1
Internet of things (IoT) connects all items to the Internet through information-sensing devices to exchange information for intelligent identification and management. Sybil attack…
Multiclass spectral feature scaling method for dimensionality reduction
Momo Matsuda, Keiichi Morikuni, Akira Imakura +2
Irregular features disrupt the desired classification. In this paper, we consider aggressively modifying scales of features in the original space according to the label information…