A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
Review and classification of emotion recognition based on EEG brain-computer interface system research: a systematic review
Recent developments and studies in brain-computer interface (BCI) technologies have
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
facilitated emotion detection and classification. Many BCI studies have sought to investigate …
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis
Intelligent fault diagnosis based on deep learning (DL) has been widely used in various
engineering practices. However, when confronting massive unlabeled industrial data …
engineering practices. However, when confronting massive unlabeled industrial data …
A comprehensive review of extreme learning machine on medical imaging
The feedforward neural network based on randomization has been of great interest in the
scientific community, particularly extreme learning machines, due to its simplicity, training …
scientific community, particularly extreme learning machines, due to its simplicity, training …
Extreme learning machine for joint embedding and clustering
Clustering generic data, ie, data not specific to a particular field, is a challenging problem
due to their diverse complex structures in the original feature space. Traditional approaches …
due to their diverse complex structures in the original feature space. Traditional approaches …
A survey of neighborhood construction algorithms for clustering and classifying data points
Clustering and classifying are overriding techniques in machine learning. Neighborhood
construction as a key step in these techniques has been extensively used for modeling local …
construction as a key step in these techniques has been extensively used for modeling local …
Multi-view clustering with extreme learning machine
Q Wang, Y Dou, X Liu, Q Lv, S Li - Neurocomputing, 2016 - Elsevier
Nowadays, data always have multiple representations, and a good feature representation
usually leads to a good clustering performance. Existing multi-view clustering works …
usually leads to a good clustering performance. Existing multi-view clustering works …
Randomnet: clustering time series using untrained deep neural networks
Neural networks are widely used in machine learning and data mining. Typically, these
networks need to be trained, implying the adjustment of weights (parameters) within the …
networks need to be trained, implying the adjustment of weights (parameters) within the …
Diagnosis of cerebral microbleed via VGG and extreme learning machine trained by Gaussian map bat algorithm
Cerebral microbleed (CMB) is a serious public health concern. It is associated with
dementia, which can be detected with brain magnetic resonance image (MRI). CMBs often …
dementia, which can be detected with brain magnetic resonance image (MRI). CMBs often …
Distributed extreme learning machine with alternating direction method of multiplier
Extreme learning machine, as a generalized single-hidden-layer feedforward network, has
achieved much attention for its extremely fast learning speed and good generalization …
achieved much attention for its extremely fast learning speed and good generalization …