A hybrid regularization approach for random vector functional-link networks

作者：

Highlights：

• Propose a new method for solving the hybrid regularization model.

• An efficient hybrid regularization algorithm is developed.

• Algorithms convergence, sparsity, and stability are proved theoretically.

• Some efficient comparisons experiments are studied.

摘要

•Propose a new method for solving the hybrid regularization model.•An efficient hybrid regularization algorithm is developed.•Algorithms convergence, sparsity, and stability are proved theoretically.•Some efficient comparisons experiments are studied.

论文关键词：Neural networks,Random vector functional-link networks (RVFL),Regularization,Sparsity,Stability

论文评审过程：Received 16 August 2018, Revised 31 July 2019, Accepted 31 August 2019, Available online 4 September 2019, Version of Record 9 September 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.112912