Efficient Inverse-Free Algorithms for Extreme Learning Machine Based on the Recursive Matrix Inverse and the Inverse LDL' Factorization

no code implementations • 12 Nov 2019 • Hufei Zhu, Chenghao Wei

The inverse-free extreme learning machine (ELM) algorithm proposed in [4] was based on an inverse-free algorithm to compute the regularized pseudo-inverse, which was deduced from an inverse-free recursive algorithm to update the inverse of a Hermitian matrix.

Efficient Ridge Solution for the Incremental Broad Learning System on Added Nodes by Inverse Cholesky Factorization of a Partitioned Matrix

no code implementations • 12 Nov 2019 • Hufei Zhu, Chenghao Wei

The proposed algorithms 1 and 2 can reduce the computational complexity, since usually the Hermitian matrix in the ridge inverse is smaller than the ridge inverse.

A Random Sample Partition Data Model for Big Data Analysis

no code implementations • 12 Dec 2017 • Salman Salloum, Yulin He, Joshua Zhexue Huang, Xiaoliang Zhang, Tamer Z. Emara, Chenghao Wei, Heping He

In this paper, we propose the random sample partition (RSP) data model to represent a big data set as a set of non-overlapping data subsets, called RSP data blocks, where each RSP data block has a probability distribution similar to the whole big data set.