0000000000674606
AUTHOR
Ajalmar R. Da Rocha Neto
showing 2 related works from this author
OnMLM: An Online Formulation for the Minimal Learning Machine
2019
Minimal Learning Machine (MLM) is a nonlinear learning algorithm designed to work on both classification and regression tasks. In its original formulation, MLM builds a linear mapping between distance matrices in the input and output spaces using the Ordinary Least Squares (OLS) algorithm. Although the OLS algorithm is a very efficient choice, when it comes to applications in big data and streams of data, online learning is more scalable and thus applicable. In that regard, our objective of this work is to propose an online version of the MLM. The Online Minimal Learning Machine (OnMLM), a new MLM-based formulation capable of online and incremental learning. The achievements of OnMLM in our…
Sparse minimal learning machine using a diversity measure minimization
2019
The minimal learning machine (MLM) training procedure consists in solving a linear system with multiple measurement vectors (MMV) created between the geometric congurations of points in the input and output spaces. Such geometric congurations are built upon two matrices created using subsets of input and output points, named reference points (RPs). The present paper considers an extension of the focal underdetermined system solver (FOCUSS) for MMV linear systems problems with additive noise, named regularized MMV FOCUSS (regularized M-FOCUSS), and evaluates it in the task of selecting input reference points for regression settings. Experiments were carried out using UCI datasets, where the …