The techniques and theories of the Extreme Learning Machines (ELM) have been developing fast with the contributions from researchers over the world in the past 10 years. ELM originally aims to fill the gap between machine learning and biological learning. ELM as a common learning mechanism may play important roles in both machine learning and biological learning irrespective of whether they are implemented in silicon, proteins or other materials. ELM theories state that as long as neurons are nonlinear piecewise continuous (even without knowing their mathematical modeling), they can be randomly generated in both artificial and biological neural networks. Random neurons may play important roles in biological learning mechanism, that is, biol...
This book contains some selected papers from the International Conference on Extreme Learning Machin...
© 2015 IEEE. Extreme Learning Machine (ELM) is an answer to an increasing demand for a low-cost lear...
Neural Networks (NN) map input data to desired output data in image processing, time series predicti...
machine learning and artifi cial intelligence relies on the coexistence of three necessary condition...
This thesis introduces novel fast learning algorithms for neural networks namely extreme learning ma...
Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer fe...
Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural network...
Nanomaterial networks have been presented as a building block for unconventional in-Materio process...
The machine learning techniques have been extensively studied in the past few decades. One of the mo...
Computational intelligence techniques have been extensively explored in wide applications in the pas...
Extreme learning machine (ELM) is known as a kind of single-hidden layer feedforward network (SLFN),...
Extreme Learning Machine (ELM) and Minimal Learning Machine (MLM) are nonlinear and scalable machine...
Artificial neural network, or commonly referred to as ''neural network'', is a successful example of...
This special issue includes eight original works that detail the further developments of ELMs in the...
Extreme learning machine algorithm proposed in recent years has been widely used in many fields due ...
This book contains some selected papers from the International Conference on Extreme Learning Machin...
© 2015 IEEE. Extreme Learning Machine (ELM) is an answer to an increasing demand for a low-cost lear...
Neural Networks (NN) map input data to desired output data in image processing, time series predicti...
machine learning and artifi cial intelligence relies on the coexistence of three necessary condition...
This thesis introduces novel fast learning algorithms for neural networks namely extreme learning ma...
Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer fe...
Extreme learning machine (ELM) has been developed for single hidden layer feedforward neural network...
Nanomaterial networks have been presented as a building block for unconventional in-Materio process...
The machine learning techniques have been extensively studied in the past few decades. One of the mo...
Computational intelligence techniques have been extensively explored in wide applications in the pas...
Extreme learning machine (ELM) is known as a kind of single-hidden layer feedforward network (SLFN),...
Extreme Learning Machine (ELM) and Minimal Learning Machine (MLM) are nonlinear and scalable machine...
Artificial neural network, or commonly referred to as ''neural network'', is a successful example of...
This special issue includes eight original works that detail the further developments of ELMs in the...
Extreme learning machine algorithm proposed in recent years has been widely used in many fields due ...
This book contains some selected papers from the International Conference on Extreme Learning Machin...
© 2015 IEEE. Extreme Learning Machine (ELM) is an answer to an increasing demand for a low-cost lear...
Neural Networks (NN) map input data to desired output data in image processing, time series predicti...