A Review on Large-Scale Data Processing with Parallel and Distributed Randomized Extreme Learning Machine Neural Networks
The randomization-based feedforward neural network has raised great interest in the
scientific community due to its simplicity, training speed, and accuracy comparable to …
scientific community due to its simplicity, training speed, and accuracy comparable to …
An Adaptive Low Computational Cost Alternating Direction Method of Multiplier for RELM Large-Scale Distributed Optimization
K Wang, S Huo, B Liu, Z Wang, T Ren - Mathematics, 2023 - mdpi.com
In a class of large-scale distributed optimization, the calculation of RELM based on the
Moore–Penrose inverse matrix is prohibitively expensive, which hinders the formulation of a …
Moore–Penrose inverse matrix is prohibitively expensive, which hinders the formulation of a …
Novel statistical regularized extreme learning algorithm to address the multicollinearity in machine learning
H Yildirim - IEEE Access, 2024 - ieeexplore.ieee.org
The multicollinearity problem is a common phenomenon in data-driven studies, significantly
affecting the performance of machine learning algorithms during the process of extracting …
affecting the performance of machine learning algorithms during the process of extracting …
TDoA Localization in Wireless Sensor Networks Using Constrained Total Least Squares and Newton's Methods
B Tausiesakul, K Asavaskulkiet - IEEE Access, 2024 - ieeexplore.ieee.org
An important service in the wireless systems for the human daily life is the information of a
mobile user location. Wireless sensor network is a structure that can be used to determine …
mobile user location. Wireless sensor network is a structure that can be used to determine …