Physical Sciences and Mathematics Commons^™

An Efficient Annealing-Assisted Differential Evolution For Multi-Parameter Adaptive Latent Factor Analysis, Qing Li, Guansong Pang, Mingsheng Shang

Research Collection School Of Computing and Information Systems

A high-dimensional and incomplete (HDI) matrix is a typical representation of big data. However, advanced HDI data analysis models tend to have many extra parameters. Manual tuning of these parameters, generally adopting the empirical knowledge, unavoidably leads to additional overhead. Although variable adaptive mechanisms have been proposed, they cannot balance the exploration and exploitation with early convergence. Moreover, learning such multi-parameters brings high computational time, thereby suffering gross accuracy especially when solving a bilinear problem like conducting the commonly used latent factor analysis (LFA) on an HDI matrix. Herein, an efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis …