Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
We present a probabilistic method for path planning that considers trajectories constrained by both the environment and an ensemble of restrictions or preferences on preferred mot...
In this paper, we propose an iterative algorithm for multiple regression with fuzzy variables.While using the standard least-squares criterion as a performance index, we pose the ...
Andrzej Bargiela, Witold Pedrycz, Tomoharu Nakashi...
—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high-resolution images based ...
Process mining techniques use event data to discover process models, to check the conformance of predefined process models, and to extend such models with information about bottl...
Wil M. P. van der Aalst, Arya Adriansyah, Boudewij...