Results 121 to 130 of about 541,400 (289)

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

Preserving bilateral view structural information for subspace clustering. [PDF]

Knowl Based Syst, 2022
Peng C, Zhang J, Chen Y, Xing X, Chen C, Kang Z, Guo L, Cheng Q.   +7 more
europepmc   +1 more source

Finding Hierarchies of Subspace Clusters [PDF]

, 2006
Many clustering algorithms are not applicable to high-dimensional feature spaces, because the clusters often exist only in specific subspaces of the original feature space. Those clusters are also called subspace clusters. In this paper, we propose the algorithm HiSC (Hierarchical Subspace Clustering) that can detect hierarchies of nested subspace ...
Elke Achtert, Christian Böhm 0001, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek   +5 more
openaire   +2 more sources

A self-training subspace clustering algorithm based on adaptive confidence for gene expression data. [PDF]

Front Genet, 2023
Li D, Liang H, Qin P, Wang J.
europepmc   +1 more source

Bursting Oscillation Characteristics and Improved AHODFC for DFIG and PMSG Combined Wind Farm

Energy Internet, EarlyView.
ABSTRACT Bursting oscillations occur in DFIG and PMSG combined wind farm under external disturbances and lead to the instability problems. To reveal the bursting oscillation characteristics and develop a suppression method, a fast‐slow dynamics analysis method and an improved adaptive high‐order differential feedback controller (AHODFC) based on ...
Kun Wang, Wei Chen, Jiangtao Li, Zhanhong Wei   +3 more
wiley   +1 more source

Deciphering the Immune Complexity in Esophageal Adenocarcinoma and Pre-Cancerous Lesions With Sequential Multiplex Immunohistochemistry and Sparse Subspace Clustering Approach. [PDF]

Front Immunol, 2022
Sundaram S, Kim EN, Jones GM, Sivagnanam S, Tripathi M, Miremadi A, Di Pietro M, Coussens LM, Fitzgerald RC, Chang YH, Zhuang L.   +10 more
europepmc   +1 more source

An Improved Fast Computational Method for Vibration Characteristic Analysis of Dry‐Type Iron Core Reactor

High Voltage, EarlyView.
ABSTRACT Structural mechanics field simulation plays a critical role in the vibration characteristic analysis of electrical equipment. Existing structural field analysis of equipment based on numerical simulation faces challenges such as convergence difficulties and prolonged computational time, failing to meet the demand for real‐time prediction of ...
Wanqing Wang, Caibo Liao, Bang Liu, Kai Li, Wenyu Liu, Zhaoguo Li, Xianfa Tian   +6 more
wiley   +1 more source

Subspace Clustering Techniques

, 2017
Subspace clustering aims at identifying subspaces for cluster formation so that the data is categorized in different perspectives. The conventional subspace clustering algorithms explore dense clusters in all the possible subspaces.
Arthur Zimek, Peer Kröger, Kröger, Peer, Zimek, Arthur; id_orcid   +3 more
core   +1 more source

How much are you willing to pay to avoid lockdowns? Evidence from the real estate market

Real Estate Economics, EarlyView.
Abstract In response to the COVID‐19 pandemic, numerous countries implemented lockdowns. In Victoria, Australia, a unique two‐tier system was employed, segregating areas with a Ring of Steel boundary and imposing additional restrictions within. This study focuses on the impact of lockdowns on housing prices and rents, exploring whether people are ...
Jian Liang, Chyi Lin Lee, Qiang Li
wiley   +1 more source

A survey on enhanced subspace clustering

, 2013
Subspace clustering finds sets of objects that are homogeneous in subspaces of high-dimensional datasets, and has been successfully applied in many domains.
Gopalkrishnan, Vivekanand, Sim, Kelvin, Cong, Gao, Zimek, Arthur   +3 more
core   +1 more source