Abstract. Smooth boosting algorithms are variants of boosting methods which handle only smooth distributions on the data. They are proved to be noise-tolerant and can be used in th...
— An iterative feature selection method based on feature typicality and interactivity analysis is presented in this paper. The aim is to enhance model interpretability by selecti...
Cyril Mazaud, Jan Rendek, Vincent Bombardier, Laur...
A wrapped feature selection process is proposed in the context of robust clustering based on Laplace mixture models. The clustering approach we consider is a generalization of the...
Nivre's method was improved by enhancing deterministic dependency parsing through application of a tree-based model. The model considers all words necessary for selection of ...
This paper presents a comparison between two technologies for reconfigurable circuits that are FPGA'se the FPAA's. The comparison is based on a case study of the area of...
Roberto Selow, Heitor S. Lopes, Carlos R. Erig Lim...