Results 271 to 280 of about 8,140,064 (302)
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2018
<p>Extreme Learning Machine (ELM) is a recently discovered way of training Single Layer Feed-forward Neural Networks with an explicitly given solution, which exists because the input weights and biases are generated randomly and never change. The method in general achieves performance comparable to Error Back-Propagation, but the training time is
Anton Akusok +6 more
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<p>Extreme Learning Machine (ELM) is a recently discovered way of training Single Layer Feed-forward Neural Networks with an explicitly given solution, which exists because the input weights and biases are generated randomly and never change. The method in general achieves performance comparable to Error Back-Propagation, but the training time is
Anton Akusok +6 more
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Information discriminative extreme learning machine
Soft Computing, 2016Extreme learning machine (ELM) has become one of the new research hotspots in the field of pattern recognition and machine learning. However, the existing extreme learning machine algorithms cannot better use identification information of data. Aiming at solving this problem, we propose a regularized extreme learning machine (algorithm) based on ...
Deqin Yan +3 more
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Reinforcement Learning Based on Extreme Learning Machine
2012Extreme learning machine not only has the best generalization performance but also has simple structure and convenient calculation. In this paper, its merits are used for reinforcement learning. The use of extreme learning machine on Q function approximation can improve the speed of reinforcement learning.
Jie Pan +3 more
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Manifold regularized extreme learning machine
Neural Computing and Applications, 2015Extreme learning machine (ELM) works for generalized single-hidden-layer feedforward networks (SLFNs), and its essence is that the hidden layer of SLFNs need not be tuned. But ELM only utilizes labeled data to carry out the supervised learning task. In order to exploit unlabeled data in the ELM model, we first extend the manifold regularization (MR ...
Bing Liu 0016 +3 more
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On the kernel Extreme Learning Machine classifier
Pattern Recognition Letters, 2015Abstract In this paper, we discuss the connection of the kernel versions of the ELM classifier with infinite Single-hidden Layer Feedforward Neural networks and show that the original ELM kernel definition can be adopted for the calculation of the ELM kernel matrix for two of the most common activation functions, i.e., the RBF and the sigmoid ...
Alexandros Iosifidis +2 more
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Extreme Learning Machine – A New Machine Learning Paradigm
In neural network theory, we analyze two strategies for learning weights: backpropagation and Extreme Learning Machine. The former is common in ANNs with one or more hidden layers, while the latter is becoming popular in ANNs with exactly one hidden layer and weights chosen based on a random selection of the weights and biases of the hidden neurons.openaire +1 more source
Hierarchical extreme learning machines
Neurocomputing, 2018Guang-Bin Huang +2 more
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Back-propagation extreme learning machine
Soft Computing, 2022Weidong Zou, Yuanqing Xia, Weipeng Cao
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Advances in Extreme Learning Machines (ELM2013)
Neurocomputing, 2015Amaury Lendasse +3 more
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Applications of Extreme Learning Machines
Computing in Science & Engineering, 2019openaire +1 more source