The nature of statistical learning theory
The nature of statistical learning theory
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
epsilon-SSVR: A Smooth Support Vector Machine for epsilon-Insensitive Regression
IEEE Transactions on Knowledge and Data Engineering
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
The Journal of Machine Learning Research
IEEE Transactions on Neural Networks
A one-layer recurrent neural network for support vector machine learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Analysis and design of primal-dual assignment networks
IEEE Transactions on Neural Networks
A One-Layer Recurrent Neural Network for Constrained Nonsmooth Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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In this paper, a generalized recurrent neural network is proposed for solving @e-insensitive support vector regression (@e-ISVR). The @e-ISVR is first formulated as a convex non-smooth programming problem, and then a generalize recurrent neural network with lower model complexity is designed for training the support vector machine. Furthermore, simulation results are given to demonstrate the effectiveness and performance of the proposed neural network.