Extreme learning machines on high dimensional and large data applications: a survey
Extreme learning machine (ELM) has been developed for single hidden layer feedforward
neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the …
neural networks (SLFNs). In ELM algorithm, the connections between the input layer and the …
Functional brain network classification for Alzheimer's disease detection with deep features and extreme learning machine
The human brain can be inherently modeled as a brain network, where nodes denote
billions of neurons and edges denote massive connections between neurons. Analysis on …
billions of neurons and edges denote massive connections between neurons. Analysis on …
Machine learning based fast multi-layer liquefaction disaster assessment
Liquefaction is one kind of earthquake-induced disasters which may cause severe damages
to roads, highways and buildings and consequently delay the disaster rescue and relief …
to roads, highways and buildings and consequently delay the disaster rescue and relief …
An overview on supervised semi-structured data classification
L Zhang, N Li, Z Li - 2021 IEEE 8th International Conference on …, 2021 - ieeexplore.ieee.org
Many collaboratively building resources, such as Wikipedia, Weibo and Quora, exist in the
form of semi-structured data. The semi-structured data has been widely used in areas such …
form of semi-structured data. The semi-structured data has been widely used in areas such …
CODES: Efficient incremental semi-supervised classification over drifting and evolving social streams
Classification over data streams is a crucial task of explosive social stream mining and
computing. Efficient learning techniques provide high-quality services in the aspect of …
computing. Efficient learning techniques provide high-quality services in the aspect of …
Text classification based on ensemble extreme learning machine
M Li, P Xiao, J Zhang - arXiv preprint arXiv:1805.06525, 2018 - arxiv.org
In this paper, we propose a novel approach based on cost-sensitive ensemble weighted
extreme learning machine; we call this approach AE1-WELM. We apply this approach to text …
extreme learning machine; we call this approach AE1-WELM. We apply this approach to text …
Uncertain xml documents classification using extreme learning machine
Driven by the emerging network data exchange and storage, XML documents classification
has become increasingly important. Most existing representation model and conventional …
has become increasingly important. Most existing representation model and conventional …
A simple, efficient and near optimal algorithm for compressed sensing
T Blumensath, ME Davies - 2009 IEEE International …, 2009 - ieeexplore.ieee.org
When sampling signals below the Nyquist rate, efficient and accurate reconstruction is
nevertheless possible, whenever the sampling system is well behaved and the signal is well …
nevertheless possible, whenever the sampling system is well behaved and the signal is well …
A positive and unlabeled learning framework based on extreme learning machine for drug-drug interactions discovery
Drug-drug interactions (DDIs) lead to Adverse Drug Reactions (ADRs) in most cases, which
increase medical costs tremendously, and may cause medical negligence or even fatal …
increase medical costs tremendously, and may cause medical negligence or even fatal …
Distributed learning over massive XML documents in ELM feature space
With the exponentially increasing volume of XML data, centralized learning solutions are
unable to meet the requirements of mining applications with massive training samples. In …
unable to meet the requirements of mining applications with massive training samples. In …