Results 211 to 220 of about 98,314 (264)

Memetic Extreme Learning Machine

Pattern Recognition, 2016
Extreme Learning Machine (ELM) is a promising model for training single-hidden layer feedforward networks (SLFNs) and has been widely used for classification. However, ELM faces the challenge of arbitrarily selected parameters, e.g., the network weights and hidden biases. Therefore, many efforts have been made to enhance the performance of ELM, such as
Yongshan Zhang, Jia Wu 0001, Zhihua Cai, Peng Zhang 0001, Ling Chen 0006   +4 more
openaire   +1 more source

Symmetric extreme learning machine

Neural Computing and Applications, 2012
Extreme learning machine (ELM) can be considered as a black-box modeling approach that seeks a model representation extracted from the training data. In this paper, a modified ELM algorithm, called symmetric ELM (S-ELM), is proposed by incorporating a priori information of symmetry.
Xueyi Liu, Ping Li 0017, Chuanhou Gao
openaire   +1 more source

In-Materio Extreme Learning Machines

2022
Nanomaterial networks have been presented as a building block for unconventional in-Materio processors. Evolution in-Materio (EiM) has previously presented a way to congure and exploit physical materials for computation, but their ability to scale as datasets get larger and more complex remains unclear.
Benedict A. H. Jones, Noura Al Moubayed, Dagou A. Zeze, Chris Groves 0001   +3 more
openaire   +2 more sources

Regularized Extreme Learning Machine

2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009
Extreme Learning Machine proposed by Huang G-B has attracted many attentions for its extremely fast training speed and good generalization performance. But it still can be considered as empirical risk minimization theme and tends to generate over-fitting model.
Wanyu Deng, Qinghua Zheng, Lin Chen 0005
openaire   +1 more source

Ordinal extreme learning machine

Neurocomputing, 2010
Recently, a new fast learning algorithm called Extreme Learning Machine (ELM) has been developed for Single-Hidden Layer Feedforward Networks (SLFNs) in G.-B. Huang, Q.-Y. Zhu and C.-K. Siew ''[Extreme learning machine: theory and applications,'' Neurocomputing 70 (2006) 489-501].
Wanyu Deng, Qinghua Zheng, Shiguo Lian, Lin Chen 0005, Xin Wang 0135   +4 more
openaire   +1 more source

A wavelet extreme learning machine

Neural Computing and Applications, 2015
Extreme learning machine (ELM) has been widely used in various fields to overcome the problem of low training speed of the conventional neural network. Kernel extreme learning machine (KELM) introduces the kernel method to ELM model, which is applicable in Stat ML.
Shifei Ding, Jian Zhang 0019, Xinzheng Xu, Yanan Zhang 0004   +3 more
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An Overview of Extreme Learning Machine

2019 4th International Conference on Control, Robotics and Cybernetics (CRC), 2019
Extreme Learning Machine (ELM), as a new learning framework of Single Hidden Layer Feedforward Neural Network (SLFN), has become one of the hottest research directions in the field of artificial intelligence in recent years. It has been widely used in multiclass classification, human action recognition and other fields.
Bohua Deng, Xinman Zhang, Weiyong Gong, Dongpeng Shang   +3 more
openaire   +1 more source

Weighted extreme learning machine for imbalance learning

Neurocomputing, 2013
Extreme learning machine (ELM) is a competitive machine learning technique, which is simple in theory and fast in implementation. The network types are ''generalized'' single hidden layer feedforward networks, which are quite diversified in the form of variety in feature mapping functions or kernels. To deal with data with imbalanced class distribution,
Guang-Bin Huang, Yiqiang Chen, Weiwei Zong   +2 more
exaly   +3 more sources

Comments on "The Extreme Learning Machine

IEEE Transactions on Neural Networks, 2008
This comment letter points out that the essence of the ldquoextreme learning machine (ELM)rdquo recently appeared has been proposed earlier by Broomhead and Lowe and Pao , and discussed by other authors. Hence, it is not necessary to introduce a new name "ELM".
Lipo Wang 0001, Chunru Wan
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Stacked Extreme Learning Machines

IEEE Transactions on Cybernetics, 2015
Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast learning speed, good generalization ability, and ease of implementation. It provides a unified solution that can be used directly to solve regression, binary, and multiclass classification problems.
Hongming Zhou, Guang-Bin Huang, Zhiping Lin 0001, Han Wang 0001, Yeng Chai Soh   +4 more
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