Buscar
Mostrando ítems 1-10 de 3853
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 ...
A metaheuristic-driven approach to fine-tune Deep Boltzmann Machines
(Elsevier B.V., 2020-12-01)
Deep learning techniques, such as Deep Boltzmann Machines (DBMs), have received considerable attention over the past years due to the outstanding results concerning a variable range of domains. One of the main shortcomings ...
Machine Learning Classifier Approach with Gaussian Process, Ensemble boosted Trees, SVM, and Linear Regression for 5G Signal Coverage Mapping
This article offers a thorough analysis of the machine learning classifiers approaches for the collected Received Signal Strength Indicator (RSSI) samples which can be applied in predicting propagation loss, used for network ...
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 ...
κ-Entropy Based Restricted Boltzmann Machines
(2019-07-01)
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 ...
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 ...
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 ...
Fine Tuning Deep Boltzmann Machines Through Meta-Heuristic Approaches
(Ieee, 2018-01-01)
The Deep learning framework has been widely used in different applications from medicine to engineering. However, there is a lack of works that manage to deal with the issue of hyperparameter fine-tuning, since machine ...
The impact of commuting time over educational achievement: A machine learning approach
(Universidad de Chile. Facultad de Economía y Negocios, 2018)
Taking advantage of georeferenced data from Chilean students, we estimate the impact of commuting
time over academic achievement. As the commuting time is an endogenous variable, we use instrumental
variables and fixed ...