Results 221 to 230 of about 98,314 (264)

Trends in extreme learning machines: A review

Neural Networks, 2015
Extreme learning machine (ELM) has gained increasing interest from various research fields recently. In this review, we aim to report the current state of the theoretical research and practical advances on this subject. We first give an overview of ELM from the theoretical perspective, including the interpolation theory, universal approximation ...
Gao Huang 0001, Guang-Bin Huang, Shiji Song, Keyou You   +3 more
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BELM: Bayesian Extreme Learning Machine

IEEE Transactions on Neural Networks, 2011
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network).
Emilio Soria-Olivas, Juan Gómez-Sanchís, José David Martín-Guerrero, Joan Vila-Francés, Marcelino Martínez-Sober, José Rafael Magdalena Benedicto, Antonio J. Serrano   +6 more
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Heterogeneous extreme learning machines

2016 International Joint Conference on Neural Networks (IJCNN), 2016
The developments in communication, sensor and computing technologies are generating information at increasing rates and the nature of the data is becoming highly heterogeneous. Accordingly, the objects under study are described by collections of variables of very different kinds (e.g. numeric, non-numeric, images, signals, videos, documents, etc.) with
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On the kernel Extreme Learning Machine speedup

Pattern Recognition Letters, 2015
We propose an approximate solution for the kernel Extreme Learning Machine.The proposed method reduces the computational and memory costs of kELM.The proposed approach achieves satisfactory classification performance. In this paper, we describe an approximate method for reducing the time and memory complexities of the kernel Extreme Learning Machine ...
Gabbouj Moncef, Iosifidis Alexandros, Gabbouj Moncef, Iosifidis Alexandros   +3 more
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Ensembling Extreme Learning Machines

2007
Extreme learning machine (ELM) is a novel learning algorithm much faster than the traditional gradient-based learning algorithms for single-hidden-layer feedforward neural networks (SLFNs). Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem.
Huawei Chen, Huahong Chen, Xiaoling Nian, Pei-Pei Liu   +3 more
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Deep kernel learning in extreme learning machines

Pattern Analysis and Applications, 2020
Emergence of extreme learning machine as a breakneck learning algorithm has marked its prominence in solitary hidden layer feed-forward networks. Kernel-based extreme learning machine (KELM) reflected its efficiency in diverse applications where feature mapping functions of hidden nodes are concealed from users. The conventional KELM algorithms involve
Afzal A. L., Nikhitha K. Nair, S. Asharaf   +2 more
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Graph Convolutional Extreme Learning Machine

2020 International Joint Conference on Neural Networks (IJCNN), 2020
Extreme Learning Machine (ELM) has gained lots of research interest due to its universal approximation capability and fast learning speed. However, traditional ELMs are devised for regular Euclidean data, such as 2D grid and 1D sequence, and thus don’t apply to non-Euclidean data, e.g., graph-structured data.
Zijia Zhang 0001, Yaoming Cai, Wenyin Gong, Xiaobo Liu 0001, Zhihua Cai   +4 more
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Learning from correlation with extreme learning machine

International Journal of Machine Learning and Cybernetics, 2019
A seemingly unrelated regression (SUR) refers to several individual equations among which there is not an explicit connection such as one equation’s observation is another equation’s response, but there exists an implicit relation represented by correlated disturbances of response variables.
Li Zhao, Jie Zhu
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Genetically optimized extreme learning machine

2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), 2013
This paper proposes a learning algorithm for single-hidden layer feedforward neural networks (SLFN) called genetically optimized extreme learning machine (GO-ELM). In the GO-ELM, the structure and the parameters of the SLFN are optimized by a genetic algorithm (GA).
Tiago Matias, Rui Araújo, Carlos Henggeler Antunes, Dulce Gabriel   +3 more
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Extreme Learning Machines with Simple Cascades

Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 2015
We compare extreme learning machines with cascade correlation on a standard benchmark dataset for comparing cascade networks along with another commonly used dataset. We introduce a number of hybrid cascade extreme learning machine topologies ranging from simple shallow cascade ELM networks to full cascade ELM networks.
Tom Gedeon, Anthony Oakden
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