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LRP-Based path relevances for global explanation of deep architectures
(Elsevier B.V., 2020)
Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information ...
kappa-Entropy Based Restricted Boltzmann Machines
(Ieee, 2019-01-01)
Restricted Boltzmann Machines achieved notorious popularity in the scientific community in the last decade due to outstanding results in a wide range of applications and also for providing the required mechanisms to build ...
Machine learning techniques to predict overweight or obesity
(2021-01-01)
Overweight and obesity are considered a public health problem, as they are related to the risk of various diseases, and also to the risk of increased morbidity and mortality. The main objective of this work was to apply ...
HOW FAR do WE GET USING MACHINE LEARNING BLACK-BOXES?
(World Scientific Publ Co Pte Ltd, 2012-03-01)
With several good research groups actively working in machine learning (ML) approaches, we have now the concept of self-containing machine learning solutions that oftentimes work out-of-the-box leading to the concept of ...
Machine Learning for Web Intrusion Detection: A Comparative Analysis of Feature Selection Methods mRMR and PFI
(2020-01-01)
Select from the best features in a complex dataset that is a critical task for machine learning algorithms. This work presents a comparative analysis between two resource selection techniques: Minimum Redundancy Maximum ...
A machine learning strategy for computing interface curvature in Front-Tracking methods
(2022-02-01)
In this work we have described the application of a machine learning strategy to compute the interface curvature in the context of a Front-Tracking framework. Based on angular information of normal and tangential vectors ...