Low-Discrepancy Points for Deterministic Assignment of Hidden Weights in Extreme Learning Machines

The traditional extreme learning machine (ELM) approach is based on a random assignment of the hidden weight values, while the linear coefficients of the output layer are determined analytically. This brief presents an analysis based on geometric properties of the sampling points used to assign the weight values, investigating the replacement of random… CONTINUE READING