Search Results for author: João P. P. Gomes

Found 5 papers, 3 papers with code

Minimal Learning Machine for Multi-Label Learning

1 code implementation9 May 2023 Joonas Hämäläinen, Amauri Souza, César L. C. Mattos, João P. P. Gomes, Tommi Kärkkäinen

Distance-based supervised method, the minimal learning machine, constructs a predictive model from data by learning a mapping between input and output distance matrices.

Multi-Label Classification Multi-Label Learning

Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection

no code implementations22 Sep 2019 Joonas Hämäläinen, Alisson S. C. Alencar, Tommi Kärkkäinen, César L. C. Mattos, Amauri H. Souza Júnior, João P. P. Gomes

Specifically, for a small number of reference points, the clustering-based methods outperformed the standard random selection of the original MLM formulation.


No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization

1 code implementation1 Aug 2019 Thiago de P. Vasconcelos, Daniel A. R. M. A. de Souza, César L. C. Mattos, João P. P. Gomes

Among the main parts of a BO algorithm, the acquisition function is of fundamental importance, since it guides the optimization algorithm by translating the uncertainty of the regression model in a utility measure for each point to be evaluated.

Bayesian Optimization

LS-SVR as a Bayesian RBF network

no code implementations1 May 2019 Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos

We show theoretical similarities between the Least Squares Support Vector Regression (LS-SVR) model with a Radial Basis Functions (RBF) kernel and maximum a posteriori (MAP) inference on Bayesian RBF networks with a specific Gaussian prior on the regression weights.


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