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Mostrando ítems 21-30 de 31
Speeding Up Evolutionary Learning Algorithms using GPUs
(ESTYLF, 2010)
This paper propose a multithreaded Genetic
Programming classi cation evaluation model
using NVIDIA CUDA GPUs to reduce the
computational time due to the poor perfor-
mance in large problems. Two di erent clas-
si ...
Herramienta Autor para la Gestión de Tests Informatizados dentro del Sistema AHA!
(Universidad de Castilla-La Mancha, Escuela Superior de Informática, 2006)
En este artículo presentamos Test Editor, una herramienta autor para la construcción de test
informatizados, tanto clásicos como adaptativos, a través del Web. Esta herramienta facilita el desarrollo y
mantenimiento de ...
Parallelization Strategies for Markerless Human Motion Capture
(2015-10-15)
Markerless Motion Capture (MMOCAP) is the
problem of determining the pose of a person from images
captured by one or several cameras simultaneously without
using markers on the subject. Evaluation of the solutions
is ...
Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learners
(Taylor & Francis, 2019)
The aim of this paper is to categorize and describe di erent types of learners in mas-
sive open online courses (MOOCs) by means of a subgroup discovery approach based
on MapReduce. The nal objective is to discover ...
Interactive multi-objective evolutionary optimization of software architectures
(Elsevier, 2018)
While working on a software specification, designers usually need to evaluate different architectural alternatives to be sure that quality criteria are met. Even when these quality aspects could be expressed in terms of ...
Educational data mining and learning analytics: An updated survey
(Wiley, 2020)
This survey is an updated and improved version of the previous one published
in 2013 in this journal with the title “data mining in education”. It reviews in a
comprehensible and very general way how Educational Data ...
JCLEC-MO: A Java suite for solving many-objective optimization engineering problems
(Elsevier, 2019)
Although metaheuristics have been widely recognized as efficient techniques to solve real-world optimization problems, implementing them from scratch remains difficult for domain-specific experts without programming skills. ...
A case-study comparison of machine learning approaches for predicting student’s dropout from multiple online educational entities
(MDPI, 2023)
Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own ...
Improving spiking neural network performance with auxiliary learning
(MDPI, 2023)
The use of back propagation through the time learning rule enabled the supervised training of deep spiking neural networks to process temporal neuromorphic data. However, their performance is still below non-spiking neural ...