AIMC Topic: Education, Distance

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Low-variance Forward Gradients using Direct Feedback Alignment and momentum.

Neural networks : the official journal of the International Neural Network Society
Supervised learning in deep neural networks is commonly performed using error backpropagation. However, the sequential propagation of errors during the backward pass limits its scalability and applicability to low-powered neuromorphic hardware. There...

Classification of mathematical test questions using machine learning on datasets of learning management system questions.

PloS one
Every student has a varied level of mathematical proficiency. Therefore, it is important to provide them with questions accordingly. Owing to advances in technology and artificial intelligence, the Learning Management System (LMS) has become a popula...

Online dynamic ensemble deep random vector functional link neural network for forecasting.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's representation ability. Ea...

Distance metric learning based on the class center and nearest neighbor relationship.

Neural networks : the official journal of the International Neural Network Society
Distance metric learning has been a promising technology to improve the performance of algorithms related to distance metrics. The existing distance metric learning methods are either based on the class center or the nearest neighbor relationship. In...

Artificial Intelligence Technologies in College English Translation Teaching.

Journal of psycholinguistic research
This paper explores the practical prospects for using artificial intelligence technologies in professional English-speaking translator education. At the online conference 'Translation Skills in Times of Artificial Intelligence' (DingTalk platform, Ja...

Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes.

Environmental science and pollution research international
Sediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer pipe hydraulic capacity and transport of pollution are the main consequences of continuous sedimentation. Among different design approaches, the non-...

Research on Online Education Resources Recommendation Based on Deep Learning.

Computational intelligence and neuroscience
For the problem of knowledge overload in the process of online learning and the traditional algorithm's poor recommendation accuracy and real-time performance in the massive educational resources, a deep learning-based recommendation model for online...

Design of Psychological Well-Being Education Environment Scheme Based on Deep Learning Theory.

Journal of environmental and public health
This paper discusses the structure of psychological well-being education programmes in higher education institutions based on an analysis of the connotation and characteristics of deep learning theory, as well as the background of today's talent trai...

Academic self-concept mediates the effect of online learning engagement on deep learning in online courses for Chinese nursing students: A cross-sectional study.

Nurse education today
BACKGROUND: Online learning is prevalent among nursing students, but the effect of online learning seems not as good as expected. Deep learning, as a learning approach that could help people solve complex problems and make innovative decisions, is as...

Application of Dynamic Process Neural Network Model Identification in Ethnic Dance Online Teaching System.

Computational intelligence and neuroscience
With the development of the times, education presents a new trend, but the teaching characteristics of dance classroom teaching cannot adapt to the current development trend. In this article, the author analyzes modern information technology, hoping ...